1

NorthGreen2017

– a marine research expedition to NE Greenland onboard ‘R/V Dana’

September 11 - October 1, 2017

Cruise report

Marit-Solveig Seidenkrantz, Jarl Regner Andersen, Katrine Juul Andresen, Jørgen Bendtsen, Camille Brice, Marianne Ellegaard, Lasse Nygaard Eriksen, Karen

Gariboldi, Cynthia Le Duc, Anders Møller Mathiasen, Tove Nielsen, Siri Ofstad, Christof Pearce, Tine Lander Rasmussen, Sofia Ribeiro, Søren Rysgaard, Hans Røy,

Caroline Scholze, Mads Schultz and David Johannes Wangner

2

Acknowledgements We thank the captain and crew of RV Dana; we are very grateful to the ship’s captain and crew as well as to the shipboard party for their hard work and help during the cruise. We are also thankful for the logistical support provided by Egon Randa Frandsen (Bioscience, AU), Peter Hersum Caspersen (DTU-Aqua), Jesper B. Rasmussen (DTU-Aqua), Linda Stuhr Christensen (DTU-Aqua), Kirsten Rosendal (Geoscience, AU), Jarl Hald (Geoscience, AU), Per Trinhammer (Geoscience, AU), Charlotte Rasmussen (Geoscience, AU), John Boserup (GEUS) and Gry Hougaard Svendsen (DTU-AQUA). Guillaume Massé (U. Laval, Canada) also provided invaluable support. The Danish Foreign Ministry, and the Government of Greenland are thanked for the permits to carry out this expedition.

The cruise was funded by the Danish Centre for Marine Research and the Natural Science and Engineering Research Council of Canada. Future research will among other be carried out through grants from the Independent Research Fund Denmark (DFF-FNU; G-Ice project), the Aarhus University Research Foundation (AUFF), and the VILLUM Foundation Young Investigator Programme (VKR023454).

Logo design by Anders Møller Mathiasen

R/V Dana in Young Sound, NE Greenland. (Photo: Claus Persson, Captain of Dana, DTU-AQUA).

Cruise track for the NorthGreen2017 expedition.

3

Table of Content Acknowledgements ................................................................................................................................ 2

Table of Content .................................................................................................................................... 3

Introduction and Aim ............................................................................................................................. 5

Cruise objectives ................................................................................................................................ 5

Scientific rationale ............................................................................................................................. 5

Research objectives ............................................................................................................................ 6

Practical Information ............................................................................................................................. 7

Cruise track ........................................................................................................................................ 7

Weather and sea-ice conditions ......................................................................................................... 8

RV Dana and shipboard equipment ................................................................................................... 8

Daily work schedule .......................................................................................................................... 9

Expedition participants .................................................................................................................... 10

Scientific party ................................................................................................................................. 10

Dana Crew ....................................................................................................................................... 11

Logistic and planning support .......................................................................................................... 11

Additional project participants ......................................................................................................... 11

Funding ............................................................................................................................................ 11

Permits ............................................................................................................................................. 11

Results .................................................................................................................................................. 12

Greenland shelf hydrography ........................................................................................................... 12

CTD and rosette water sampling .................................................................................................. 12

Acoustic Doppler current profiler ................................................................................................ 12

Sea ice, icebergs and rivers .......................................................................................................... 13

Mooring deployment .................................................................................................................... 13

Turbulence measurements ........................................................................................................... 13

Underway CTD ............................................................................................................................ 14

Mesozooplankton analyses .............................................................................................................. 14

MIK net ........................................................................................................................................ 14

Multinet ........................................................................................................................................ 14

Chlorophyll measurements .......................................................................................................... 15

WP3 net ........................................................................................................................................ 15

Planktic Foraminiferal distribution and ecology .............................................................................. 16

Sea-ice proxy development .............................................................................................................. 17

Sea floor morphology: Shallow seismic acquisition ........................................................................ 19

4

Sediments ......................................................................................................................................... 22

Sediment sampling equipment ..................................................................................................... 23

Results of sediment sampling – Summary per station ................................................................. 27

Geomicrobiology ............................................................................................................................. 30

Microplastics in deep sea sediments ................................................................................................ 32

Living and recent benthic foraminifera ............................................................................................ 32

Seabird and marine mammal survey in the Greenland Sea ............................................................. 34

Examples of future analyses ................................................................................................................ 35

Educational perspective ....................................................................................................................... 35

Post cruise meeting .............................................................................................................................. 35

References ............................................................................................................................................ 36

Appendix 1. Samples collected for sea-ice proxy development .......................................................... 37

Appendix 2. Sediment cores – deployment and recovery.................................................................... 41

Appendix 3. Surface sediment recovery .............................................................................................. 45

Appendix 4. Detailed lists of all casts deployed during the NorthGreen2017 Expedition .................. 47

5

Introduction and Aim From September 11 – October 1, 2017, the research vessel ‘Dana’ (Hirtshals, Denmark) served as a platform for a 5576 km long Danish-Greenlandic-Canadian-Italian-Norwegian multi-disciplinary research expedition off Northeast Greenland. The expedition combined research in oceanography/hydrography, bioscience and geoscience. In total, 20 scientists and students from the participating countries partook in the cruise, in addition to 18 crew members. The cruise was funded by the Danish Centre for Marine Research, with co-funding from the Natural Science and Engineering Research Council of Canada. Cruise objectives The aim of the expedition was to study past and current changes in Arctic ice shelves, ocean circulation, sea-ice extent, sediment transport and freshwater discharge from the Greenland ice cap as well as the impact on biota, pelagic/benthic ecosystems and microbial processes. For this purpose a range of different data and samples were collected, in particular CTD data, turbulence measurements, water samples, sea ice samples, phyto- and zoo-plankton samples as well as sea-floor sediments and sediment cores from this hitherto little explored region of NE Greenland. The NorthGreen2017 expedition thus provided a unique set of data and material for further study from the north-eastern coastal regions of Greenland. Scientific rationale Northeast Greenland is a key region for studying past sea-ice variability and glacier melt-off and their impact on the environment and biota. Nevertheless, the Northeast Greenland shelf has hitherto been very little explored due to its remote location and the normally heavy sea-ice conditions. The present expedition and the exceptionally low late September sea-ice cover this year made it possible to reach areas of the NE Greenland shelf that had hitherto been only little studied, to collect data and material that will help resolve a number of scientific questions in a wide range of subjects, all related to sea ice and climate conditions. Greenland shelf hydrography. A number of studies exist on the modern water mass distribution in the Fram Strait1,2. However, very little is known about the hydrography of the Northeast Greenland shelf itself, with only few studies providing information, mostly on the ice-free regions3. Deployment of CTD casts, turbulence measurements and collection of water samples from several depths through the water column in transects across the Greenland shelf as well as deployment of underway CTD (uCTD) for near-continuous measurements of water properties during the expedition, made it possible to identify and separate the various water masses found on the NE Greenland shelf. This study is essential for the understanding and interpretation of all other analyses carried out on material from this cruise.

Palaeoclimate/oceanography, sea-ice cover, glacier melting. In wide areas of the Arctic, rapid warming affects both oceanic and atmospheric conditions. Sea ice has been strongly diminishing for the last >30 years and Greenland glacier melting has increased4, both phenomena surpassing expectations based on temperature alone5. Yet, little is known about the natural variability of sea-ice cover and glacier melting rates at multi-decadal to millennial timescales, and there is a lack of a preindustrial “baseline”, although the few available reconstructions of past Arctic sea ice indicate that the recent sea-ice extent is smaller than centennial to millennial averages6-8. Hence, a better understanding of the mechanisms that govern sea-ice variability and glacier melting, as well as the potential role of increasing ocean temperatures on glacier melting9,10 is necessary for improving forecasting. Also, we have little information on the stabilising effect of sea ice on North Greenland glacier ice mélange and ice shelves11. Changes in albedo linked to reduced sea-ice cover may cause

6

positive feed-back processes and warming of the Arctic Ocean12, while increased glacier melting may cause a further freshening of the Arctic ocean surface waters, also affecting the salinity of polar water exported to the North Atlantic13. Both mechanisms may thus potentially reduce deep-water formation and the global ocean circulation.

Sea floor land forms, glacier extent and sediment deposition. The reconstruction of glacial advances and retreat on the East Greenland shelf/margin and their links to past climatic fluctuations need to be further constrained by glacial geological mapping14. The limited investigations of shelf regions of NE Greenland means that seafloor morphological and Quaternary sediment records, despite some recent progress15, are scarce due to the lack of acoustic data and cores. This expedition has provided high resolution sub-bottom profiler data that, together with sediment cores also collected during the cruise as well as existing multibeam data15, informs on geometry, dynamics and chronology of the extension and retreat of ice sheets in this key area and thereby greatly increase our knowledge on the palaeoglaciology of the NE Greenland margin.

Phyto- and Zooplankton. The biogeography of marine waters along much of the Greenland margins is relatively well studied thanks to international efforts16,17, but data are still limited on the modern living conditions of several of the organisms, such as copepods, planktic foraminifera, dinoflagellates, ciliates, and diatoms, that make out an important part of the biodiversity and are important in palaeo records. Also, the signal of these organisms recorded in the sediment may not always represent the actual conditions in the surface waters due to current transport. Combining data from plankton netting (planktic foraminifera, dinoflagellates, and copepods), CTD water sampling (diatoms, ciliates, dinoflagellates) and surface sediments from Haps/Rumohr cores collected during the cruise, we will be able to compare living communities with the assemblages found at the sea floor. This will not only provide additional information on the living phyto- and zooplankton communities, but will also inform on the sedimentation and preservation potential of plankton. Geomicrobiology. Northeast Greenland waters are unique in the Atlantic system because the bottom waters are permanently near the freezing point of seawater (ca -1.5°C), and because the currents that enter the area all come from similarly cold regions. This makes the region ideal for the study of the geobiology of cold-adapted benthic prokaryotes without the interference of mesophiles that might prosper in warm seasons or be brought by currents from elsewhere. Sediments collected in such cold regions during the expedition, will thus make it possible to compare microbial communities from such cold sites with those of sites located in areas swept by warmer bottom currents. Research objectives The main scientific objectives of the cruise and the post-cruise research are: 1. To characterize present sea and glacial ice, ocean circulation, water mass physical and optical properties and ocean-atmosphere exchanges through hydrographical investigations. 2. To document change in climate and ocean circulation over the last ~100,000 years using a multiproxy approach based on a comprehensive set of marine sediment archives. 3. To reconstruct the history of growth and decay of ice sheets on the NE Greenland continental shelves as well as glacier melting rates through the study of sediment cores, and to document modern glacial sedimentary processes on the NE Greenland shelf. 4. To document morphological and lithological record of glacial and sedimentary processes on the sea floor via high-resolution acoustic measurements. 5. To describe and understand the functioning of the marine ecosystems in sea-ice covered environments and determine the impact of current and near-future changes in the Arctic environment on marine ecosystems and biogeochemical fluxes using plankton net, sea-floor sediments, water samples and hydrographical data.

7

6. To describe and compare microbial communities using both genetic diversity and traditional taxonomical tools, with those from previously studied locations of the Canadian Arctic in relation to environmental variables. 7. To test if the high rates of microbial activity in the cold seabed is explained by specially adapted microbes or by high numbers.

Practical Information The three week long NorthGreen2017 expedition was carried out as Leg 2 of a six week cruise of RV Dana to NE Greenland. Leg 1 was carried out in the context of a monitoring project by the Government of Greenland. The combination of the two cruise legs, made it possible to save significant transit time for both expeditions. Cruise track The scientific party of the NorthGreen2017 expedition embarked in Longyearbyen, Svalbard, Norway and disembarked in Hirtshals, Denmark (home port of RV Dana). The total track of the expedition covered 5576 km, thereof 2475 km as research and 3101 km in transit from Longyearbyen to Station 1 and from NE Greenland (St. 29) to Hirtshals. A map with cruise track and sampling sites is given Fig. 1 and detailed lists of samples are shown in Appendices 1-4.

Due to strong winds, the stations originally planned on the abyssal plane, slope and outer shelf on the transit towards NE Greenland had to be cancelled, and we continued landward across the shelf in order to reach the calmer waters close to the sea ice. From then on, operations ran smoothly, although the location of sea ice heavily controlled the cruise track and the location of stations until ca. 76°N. Due to exceptionally low sea-ice conditions off NE Greenland during the time of the cruise (see below), it was possible to reach as far north as 80°N. Thus, the expedition spent the first days between 80 and 79 °N,

after which the expedition gradually moved southwards, finally reaching the Young Sound region. However, gale-force winds and a weather forecast promising fairly strong storms in the Greenland-Norwegian Seas forced the expedition to depart one day early from the study area in order to circumvent the predicted low pressure area via a somewhat longer route towards Hirtshals. Consequently, the expedition arrived in Hirtshals almost one day earlier than planned.

Fig. 1. Cruise track, excl. transits. The purple line shows the transits during which Innomar® shallow seismics, ADCP and echosound data were collected. Yellow dots show the location of stations for collection of CTD, water samples, plankton net and/or sediments. The bathymetrical map is based on GEBCO18.

8

A second parameter for choosing station locations was a detailed study of the known bathymetry18,19, in order to increase the chances of finding thick Holocene and late Glacial sediment packages in depressions. Subbottom surveys (Innomar® seismic profiler) were among other used to identify the best possible coring sites within the chosen target areas. Weather and sea-ice conditions The cruise was planned for September due to the minimum sea-ice conditions normal for this month. In fact, record low sea-ice cover meant that it was possible to work in a larger area than expected, up to 80°N. Daily ice charts (Fig. 2) kept the expedition abreast of ice conditions, providing the information needed to plan the best possible route for the ship. The late September timing, however, also meant that the risk of strong winds or even storms was fairly high. Despite relatively high wind speeds west of Svalbard, only 1.5 days of work time was lost to bad weather; 0.5 of these days was used to carry out a more extensive Innomar® and uCTD study of Young Sound. Consequently, only the last day of research time was lost due to weather, as Dana had to depart NE Greenland one day early due to an upcoming storm. RV Dana and shipboard equipment The RV Dana (Fig. 3) belongs to the National Institute of Aquatic Resources (DTU-Aqua), Denmark. The ship is 78.43 m long, 14.7 m wide and has a brute tonnage of 2545 GT and accommodates 38 persons (crew and scientists). Dana is equipped with a CTD (SBE19+, Seabird), an Innomar SES-2000 Deep Narrow-Beam Parametric Sub-Bottom Profiler system (on loan from GEUS) as well as a 50 µm multinet (four nets available for the cruise), a WP3 net and a Methot Isaac Kidd (MIK) net. In addition, members of the expedition also brought two nets of 20 µm mesh size for the multinet. An underway CTD (uCTD; provided by ClimateLab) was deployed in the Young Sound area and across the shelf, as conditions here were ice free. A micro-scale turbulence profiler (VMP-250) was applied at the CTD-stations (also provided by ClimateLab.

For sediment sampling, a 6-m Gravity corer and a Rumohr lot corer from the Center for Geomicrobiology, AU, were deployed using the ship’s main winch. A backup Gravity coring system from GEUS was also brought on the expedition, but it was never used. A Box corer from GEUS was deployed at the first station, but due to equipment problems, a Haps corer system from DTU-AQUA was deployed at all following sediment stations. Due to the smaller size of the Haps corer; 3 Haps deployments equalled one box corer in surface sediment retrieval.

Fig. 2. Example of sea ice chart provided daily by the Danish Meteorological Institute. The green line shows the sea-ice extent on that given day. Source: Danish Meteorological Institute.

Fig.3. R/V Dana in Young Sound, NE Greenland. Photo: Claus Persson, Captain of Dana, DTU-AQUA.

9

Daily work schedule The expedition was carried out as a 24-hour operation. After the first couple of stations the best procedures for use of equipment and collection of data was established, and it became possible to follow a semi-standard work programme for most of the remaining cruise. Except for the last research day, which was solely allocated to establishing a CTD transect across the Greenland shelf (from Young Sound to the foot of the slope), one full station and one or more special stations were carried out each day. Full station: When possible, stations were sampled with the following program: 2 CTD/rosette, 1 turbulence profile (VMP-250), 2 casts of 50-µm multinets, 1 cast of 20-µm multinet, 3-7 Rumohr cores (also called Rumohr Lot), 1 Gravity core, 3-5 Haps cores. The remainder of the time was allocated Innomar® seismic investigations as well as a MIK net and CTD programme around midnight. Special station: If the Innomar® seismic survey had identified more than one potentially good coring site, a second site was visited for a sediment coring (2-3 Rumohr cores, 1 Gravity core), if time permitted. In addition, some stations were purely allocated to CTD and water collection. Typical daily work programme: 04.00 Ship in vicinity of pre-selected station.

Shallow seismic site survey in the area selected for next station. 08.00 Final station location handed to Bridge; selection carried out based on Innomar®

investigations. 08.15 At station. Start water and plankton programme:

CTD/rosette (collection of water samples) Turbulence measurements CTD/rosette (collection of water samples close to the surface) Multinet (50 µm) for collection of living copepods and other mesozooplankton Multinet (50 µm) for collection of living planktonic foraminifera Multinet (20 µm) for collection of living phytoplankton

12.00 Start sediment programme: 3-7 Rumohr lot (3 for palaeoclimate, 2 for geomicrobiology, 2 for eDNA studies). 1 Gravity core 3-5 Haps cores (for collection of surface samples for a range of analyses). 16.30 Proceed to extra site (special station), if such a site had been identified: 2-3 Rumohr lot 1 Gravity core 19.00-04.00 End of operations; Start Innomar® and transit to next planned station. 19.30 Science talk/seminar by 1-2 expedition participants. 24.00-02.00 CTD and MIK net (during long transits the MIK net and CTD/water stations were

omitted)

10

Expedition participants Scientific party The scientific party (Fig. 4) was divided into several work teams, each headed by a senior scientist with students and early-stage researchers rotating among the teams to gain maximum experience. The shipboard scientific party consisted of twenty scientists and students: Andersen, Jarl Regner AU(Bio), Denmark Responsible for birds and marine mammal monitoring Andresen, Katrine J. AU(Geo), Denmark Responsible for Innomar® seismic programme (days) Bendtsen, Jørgen ClimateLab Responsible for CTD and turbulence programme. Brice, Camille UQAM, Canada MSc student Ellegaard, Marianne KU(Bio), Denmark Co-responsible for eDNA programme Eriksen, Lasse Nygaard AU(Geo), DK MSc student Gariboldi, Karen U. Pisa, Italy Postdoc, responsible for surface sediment sampling Le Duc, Cynthia UQAM, Canada MSc student Mathiasen, Anders Møller AU(Geo), DK MSc student Nielsen, Tove GEUS Responsible for Innomar® seismic programme (nights) Ofstad, Siri UiT, Norway PhD student, responsible for planktic foraminiferal programme Pearce, Christof AU(Geo), Denmark Responsible for sediment collection and treatment Rasmussen, Tine L. UiT, Norway Responsible for preliminary site selection (night). Ribeiro, Sofia I. GEUS Co-responsible for eDNA programme Rysgaard, Søren AU(ARC), Denmark Responsible for water collection programme. Røy, Hans AU(Bio), Denmark Responsible for sediment coring and geomicrobiology programme Scholze, Caroline AU(Bio), Denmark PhD student; co-responsible for geomicrobiology programme Schultz, Mads AU & DTU, DK MSc student; overall responsible for the plankton net programme Seidenkrantz, Marit-Solveig AU(Geo), Denmark Chief scientist Wangner, David Johannes GEUS PhD student

Fig. 4. The scientific party onboard RV Dana at 80°N. (Photo: Christian Petersen; edits: Christof Pearce). Back row, from left to right: Jørgen Bendtsen, Lasse Nygaard Eriksen, Anders Møller Mathiasen, Søren Rysgaard, Hans Røy. Middle row, from left to right: Mads Schultz, David Wangner, Katrine Juul Andresen, Tove Nielsen, Tine Rasmussen, Marianne Ellegaard, Marit-Solveig Seidenkrantz, Sofia Ribeiro, Jarl Regner Andersen. Front row, from left to right: Christof Pearce, Caroline Scholze, Cynthia Le Duc, Camille Brice, Karen Gariboldi, Siri Ofstad.

11

Dana Crew Captain of Dana: Claus Persson, DTU-AQUA. Dana Crew: Anna Kvalsøe Andersen, Per Christensen, Lars Olen Dybager, Jacob Vangsgaard, Jan Conrad, Jesper Houggaard Hansen, Mikkel Hansen, Anton Juul Jensen, Maj-Brit Sick Jensen, Allan Lilleøre, Michael Markvart, Dan Mikkelsen, Eik Moen, Jette Mortensen, Christian Petersen, Søren Rasmussen, Jesper Thomsen. Logistic and planning support Logistic support was provided by: Egon Randa Frandsen (Arctic Research Centre, AU), Peter Hersom Caspersen (DTU-AQUA); Linda Stuhr Christensen (DTU-AQUA), Jesper B. Rasmussen (DTU-AQUA), Kirsten Rosendal (Geoscience, AU), Jarl Hald (Geoscience, AU), Per Trinhammer (Geoscience, AU), Charlotte Rasmussen (Geoscience, AU), John Boserup (GEUS) and Gry Hougaard Svendsen DTU-AQUA. Thank you to all. Early planning stage consultancy was provided by Guillaume Massé (University of Laval, Canada), Patrick Lajeunesse, (U. Laval, Canada), Philippe Archambault (Université de Québec à Rimouski, Canada). Additional project participants Camilla S. Andresen (GEUS, Denmark), P. Archambault (UQAR, Canada), Anne de Vernal (UQAM, Canada), Hui Jiang (ECNU, China), Antoon Kuijpers (GEUS, Denmark), Patrick Lajeunesse (U. Laval, Canada), Guillaume Massé (U. Laval, CNRS, Canada), Caterina Morigi (U. Pisa, Italy), Anders Mosbech (Bioscience, AU), Eva Friis Møller (Bioscience, AU), Torkel Gissel Nielsen (DTU-Aqua, Denmark), Ralph Schneider (Kiel U., Germany), Marie-Alexandrine Sicre (L’Ocean, Paris, France), Kaarina Weckström (U. Helsinki, Finland).

Funding Danish Centre for Marine Research (grant to Marit-Solveig Seidenkrantz and co-applicants; 2,804,000 DKK) Natural Science and Engineering Research Council of Canada (grant to Anne de Vernal and co-applicants; 950,000 DKK).

Pre-cruise requirements All cruise participants underwent a course in “safety-at-sea” (STWC 1.1 certificate) and a health check (“Den Blå Bog” or “the Danish Maritime Authority’s Medical certificate for examination of seafarers”) prior to the cruise. In addition, the entire ship-board party participated in a 3-hour course in first aid and fire management taught by Jesper B. Rasmussen (DTU-AQUA) in Longyearbyen, Svalbard.

Permits Permits for this cruise and collection of data were received from the following organisations:

• Ministry of Nature and Environment, Government of Greenland (permit no. C-17-61; permit to enter the National Park).

• Ministry of Industry, Labour and Trade, Government of Greenland (permit no. C-17-61; permit for biological investigations)

• Mineral Licence and Safety Authority, Government of Greenland (permit no: VU-00125; permit for geological investigations).

• Export permit from Mineral Licence and Safety Authority, Government of Greenland (permit no: 129/2017; permit to collect and export sediments).

• Ministry of Foreign Affairs, Government of Denmark (permit to enter the 12 and 3 NM zones off NE Greenland.

12

Results Analyses and collection of material and data were carried out at 29 different stations on the NE Greenland shelf from 80°N to 74°N.

Greenland shelf hydrography by Jørgen Bendtsen and Søren Rysgaard CTD and rosette water sampling We used a rosette with 12 bottles to collect water (Fig. 5) at different depths in the water column to be sampled at 1 m, 5 m, 10 m, 20 m, deep chlorophyll maximum, 30 m, 50 m, 100 m, 200 m, 400 m and bottom. A CTD (Seabird 911 system) attached to the rosette measured conductivity, temperature, fluorescence and pressure, to characterize temperature, salinity and chlorophyll conditions at different depths and to identify different water masses. In addition, two oxygen sensors and a light meter were mounted on the rosette. Two CTD/rosette casts were launched at each station. The first collected water from all targeted depths (whenever water depth allowed), whereas the second one collected several bottles from surface water and the maximum chlorophyll water depth. At every station, we collected the following water samples: • 3 plastic bottles of 500 ml for micro-plastic analyses at 1 m, 30

m and 100 m. • 22 vials of 50 ml for carbonate system analyses (dissolved

inorganic carbon and total alkalinity) at all depths to which we added 50 µL of HgCl (5% solution).

• 4 plastic bottles of 100 ml for Mg/Ca analyses at 1 m, DCM, 200 m and 400 m to which we added 0,5 ml of HNO3 (36% solution).

• 11 plastic bottles of 50 ml for nutrients analyses at all depths and frozen for later analysis (silicate, nitrate, phosphorous).

• 11 glass vials of 2 ml for 18O:16O and 2H:1H analyses. • 3 plastic bottles of 10 L for DNA and microplankton analyses at

1 m, DCM, and 400 m. • 3 amber bottles of 250 ml for microplankton assemblages at 1

m and DCM to which we added 2 ml of lugol. • 5-6 plastic bottles of 1 L (whenever possible) for mesoplankton

at 1 m, 30 m, DCM, 50 m, 100 m and 200 m. Acoustic Doppler current profiler A ship-mounted 75 Khz Acoustic doppler current profiler (RD instruments) continuously measured from station 5 (15 September) and until the end of the cruise (station 29). Some interruptions in the data sampling during the first days were necessary for testing for possible interference with some of the other acoustic measurements on board. However, no interference was found. The ADCP measures currents in the water column and will be applied in the analysis of transports of water masses along the shelf.

Fig. 5. Water sampling from CTD rosette. Photo: Anders Møller Mathiasen.

13

Sea ice, icebergs and rivers Sea ice and icebergs were also sampled (Fig. 6) for analysis of 18O:16O and 2H:1H , nutrients and total alkalinity whenever possible. Small drifting ice pieces were collected with a net from the deck of DANA. Runoff from land was collected in a small creak below its frozen surface in Daneborg (Young Sound) for similar analysis. Mooring deployment A hydrographic mooring was deployed (Fig. 7) outside Young Sound to record the annual conditions of temperature, salinity and pressure. The moorings was deployed at GH10 (74°04.880’N, 19°08.855’W). The mooring is recording temperature, salinity and pressure at 25 m depth, 100 m and 200 m depth. The idea behind deploying the moorings is to resolve the seasonal and inter-annual variation in hydrographic conditions in the fjords and the Greenland Sea. At present data on the seasonal and annual variability in fjords connecting the Greenland Ice Sheet and the Greenland Sea is absent. The moorings will replace our moorings from last year and we hope to continue the records in this remote area.

Fig. 7. Tube mooring being deployed from Dana during the NorthGreen2017 expedition. The tubes are collecting data from several water depth levels year round. The design allow for measuring hydrographical conditions in waters with sea ice and icebergs. The tube will slide below moving ice and rise again after its passage. Photo: Cynthia Le Duc).

Turbulence measurements Turbulence and micro-structure measurements (Fig. 8) were out at 15 stations by a VMP-250 (Rockland Science) profiler. The turbulence-profiler measures vertical shear, temperature and conductivity at a high sampling rate and in addition it has a regular CTD-sensor. The dissipation rate of turbulent kinetic energy can be calculated from the velocity shear and, thereby, the vertical turbulent fluxes of heat, nutrients, tracers and other dissolved substances can be determined. Microstructure of temperature and salinity provides an independent estimate of turbulence in the water column down to the centimeter scale. Turbulent vertical fluxes will be included in the water mass analysis and the general description of mixing processes in the East Greenland Current System.

Fig. 6. Collection of ice for stable isotope and plankton analyses. Photo: Christof Pearce.

Fig. 8. Deployment of VMP-250 turbulence profiler (Photo by Søren Rysgaard)

14

Underway CTD We applied an Underway CTD (uCTD; Fig. 9) (Ocean Science) for high-resolution CTD-measurements. The uCTD was applied during three transects in Young Sound, where the instrument was measuring the upper 60 m of the water column. This gave a high spatial resolution of temperature and salinity changes across the pycnocline in the fjord. A high-resolution transect with combined CTD and UCTD-measurements was conducted from Young Sound and across the shelf to the slope. These hydrographic measurements will enable us to analyze mixing between near-coastal water masses and water further out on the shelf. Furthermore, they will be analyzed for calculating currents and transports on the shelf.

Mesozooplankton analyses by Mads Schulz MIK net The Methot Isaac Kidd (MIK) net gathers information of the top 100 meters of water column by combining a nightly sampling of zooplankton, with a special focus on krill, with echo sound. The data were collected for Eva Friis Møller (Bioscience, AU), who carried out a more intense survey during the first cruise leg of the Dana NE Greenland expedition. The MIK net was set to sample in a V-shape, going to a hundred meters water depth and back up again. For each MIK net trawl sampling time was approximately 35 minutes, with a release of the net at 30 m/min and a haul in at 12.5 m/min meanwhile sailing at a speed of 3 knots. As the focus was mainly on krill for this study, the trawls were carried out during night time in anticipation of the vertical migration of the circadian rhythm rates in krill. A total of five MIK net samples were collected. The samples were not further analysed on board, as analyses are planned to be carried out post-cruise at the Department of Bioscience, Aarhus University. Multinet The temporal and geographical placement of the NE Greenland cruise, both Leg 1 and Leg 2, created an opportunity to describe the abundance and vertical distribution in fixed depths for zooplankton species, with a special focus on copepods and the stages represented in the genus Calanus. A total of 12 successful multinet casts (Fig. 10; Appendix 4) for macro zooplankton analyses were carried out. The depths sampled during the cruise were bottom- 200m, 200-100m, 100-50m and 50m-surface. These depths were chosen as representatives for the surface living copepods expected to be in the Depth for Chlorophyll Maximum (DCM), as well as the deeper intervals in between 50 and 200 meters. The bottom-200m measure is assumed to represent copepods undergoing diapause and the survey aims to test for a possible vertical

Fig. 9. Deployment of Underway CTD from the aft. Photo: Søren Rysgaard.

Fig. 10. Deployment of multinet from Dana. Photo: Christof Pearce.

15

distribution as diapause was entered. As the life stage of the species is included in this abundance survey, the vertical distribution can show if some stages enter diapause earlier. Samples collected via the Multinet will be analysed as part of an MSc project by Mads Schultz upon returning to Denmark. Chlorophyll measurements The measuring of chlorophyll via fluorometer plays a part in the initiation of diapause experiments, as well as contributes to a survey continued from the first cruise leg, during which Mikael Sejr (ARC, AU) carried out the sampling. Chlorophyll was measured from filtering 250 mL onto GF/F and 500 mL onto a 10 µm filter. The depths of these measurements were 1 m, the DCM, 50 m and 100 m. WP3 net The WP3 net (8 casts) was used for collecting samples from various depths, ranging from 400 meters to the surface. Samples collected via WP3 nets have been used for three different experimental setups, all focusing on the lipid content of Calanus hyperboreus (Fig. 11) and their activity levels. Experiment: Initiation of diapause Aim: This experiment is conducted to show the activity level of the surface living C. hyperboreus as a function of time and geographical distribution (experiment is conducted on both cruise legs), as well as the activity level for the late surface living individuals as a function of life stage, food availability and lipid store. Furthermore, we evaluate if grazing can be induced in individuals that have already left the surface waters. For all stations, lipid store will be compared between surface living and deep (descending or diapausing) copepods. Method: Upon selected locations, surface (0-100 m) and deep (200-400 m) sampling of C. hyperboreus was conducted. The individuals were sorted and divided into different life stages. During the sorting, at least 10 individuals of each life stage were singularly introduced to 600 mL containers, containing in situ water retrieved from the DCM. The containers were mixed every 8th hour, ensuring low amounts of algal sedimentation. For every single individual, fecal count was carried out after a 24-hour period and the C. hyperboreus were photographed for size and lipid content determination. Preliminary results: The cruise enabled sampling for this experiment at stations 1, 3, 7, 8, 12, 13, 14, 16 and 19. The lipid content will be derived upon the return to Denmark. Experiment: Termination of diapause Aim: This experiment was conducted to evaluate the role of lipid content in the beginning of the egg production. Method: At selected location, near bottom sampling of C. hyperboreus were conducted. The individuals were sorted and only females were kept for the experiment. The females were photographed for lipid content measurements and then introduced to flat 90 mL solo containers with filtered sea water where they were stored at 3 different temperatures, 0°C, 3°C and 5°C. An optical cord was mounted on 3 containers from each temperature level for oxygen measurements (this is purely an indication of oxygen availability and not an experiment on the diapause metabolism). All individuals were examined for egg production every third day. At the first sign of egg production, lipid levels were measured by photographing the given individuals. At the end of the cruise, the specimens were transported to the laboratory location using thermos regulated cooling boxes. The experiment is continued in the laboratory of Aarhus University, Denmark. Beside this, the number of produced eggs were measured and compared to the lipid stores. Preliminary results: For each storage temperature (0°C, 3°C and 5°C) 20 copepods sampled from the top 100 meters and 30 sampled from 400-200

Fig. 11. Calanus hyperboreus. Photo: Mads Schulz.

16

meters were kept in separate bottles. At the end of the cruise, egg production had occurred in 1 bottle from 3°C and one bottle from 5°C. Experiment: Initiation of ascend Aim: This experiment was designed to show ascending trends, testing the theory that diapausing individuals are not as effective at feeding within the first 12 hours, as ascending individuals are. Temperature differences was added to connect increased metabolism along with the decrease in lipid stores, to the determination of diapause. Method: Upon selected location, near bottom sampling of C. hyperboreus were conducted. The individuals were sorted and only individuals of stage CIII, CIV and CV are kept for the experiment. The selected specimens were divided into 12 flasks, each containing 30 individuals. For each flask, mean lipid content was measured. The flasks were stored in darkness at 3°C. After termination of the cruise, all samples were brought to the laboratory on land, and kept at 3 different temperatures, 0°C, 3°C and 5°C. Start October, one flask from each temperature will be transferred to a feeding chamber, along with and algae culture. Faecal counts were conducted after 12 hours of possible forage time. This was repeated with one month interval, so experiments were conducted in October, November, December and January. After each feeding experiment, lipid stores were determined and the new mean was connected to the start mean and subsequently compared to temperature and storage time intervals along with faecal count for the 12 hours. Preliminary results: The copepods used for this experiment were collected at Station 3 of the second cruise leg.

Planktic Foraminiferal distribution and ecology By Siri Ofstad Plankton net samples were collected at each full station using a Multinet (multi-stratified plankton tow Hydrobios, type Midi) equipped with four 50-μm nets (11 casts; Appendix 4). At each collected station four depth intervals were sampled in one stroke, dividing the water column into the following depths intervals: 300/400-200 m, 200-100 m, 100-50 m, and 50-surface. The contents of each cast were sieved on a 63 um sieves and placed in separate 200 ml bottles using filtered seawater (Fig. 12). Samples were preserved in 96% ethanol solution and buffered with hexamethylenetetramine. Calcifying organisms, including planktic foraminifera, pteropods and bivalves, will be studied from the collected samples. In addition to study the general temporal distribution of planktic foraminiferal species, a particular interest will be given to their shell structure (CaCO3) with regard to the ocean chemistry (e.g. DIC, TA, pH). The small mesh size and coverage of the entire water column allows the analyses of other zooplankton groups (e.g. copepods, dinoflagellates, cladocerans), which provide additional information about water masses dynamics in North East Greenland. In addition to the multinet samples, surface sediment samples (top 1-2 cm) were taken from the Haps at each station where a multinet was taken. The samples (5-10 ml), were spooned into small ziplock bags and stored in the cooling room. The sediments will be sieved and analysed for planktic

Fig.12. Multinet sampled on the sieve before it is transported to the sample bottle (right), sample bottles from one station (left). Photo: Siri Ofstad.

17

foraminifera upon return to land. It is important that we get a full picture of what is happening in the water column with regard to the planktic foraminiferal community, including after their lifecycle comes to an end. Planktic foraminifera found in the surface sediment will be used to establish the flux of organisms from water column to seafloor. Fossilized planktic foraminifera may be used for carbonate system reconstructions, as an attempt to quantify ocean acidification.

Sea-ice proxy development By Sofia Ribeiro and Marianne Ellegaard The overall aim of our sampling campaign and studies following this cruise are to refine and develop micro-algal proxies of Arctic sea-ice cover. Microalgae, particularly diatoms and dinoflagellates, are the sources of the most used sediment core proxies for reconstructing past sea-ice cover (i.e. dinoflagellate cysts, diatom valves, and biomarkers such as IP25). However, much is not known about the biology, taxonomy, and complexity of ecological responses of these proxies. Objectives 1. To establish the biological affinity and habitat (sea ice vs. water) of the different life-cycle stages for unknown or poorly known cyst-forming dinoflagellates and evaluate their potential as sea-ice indicators. Target groups include the autotrophic ice-dwelling species Polarella glacialis, and the genera Protoperidinium/Islandinium/Brigantedinium. Samples: Water, plankton, and surface sediments where collected for this purpose (Appendix 1; Fig. 13). Additionally, we obtained chunks of sea ice sampled on-route (by Søren Rysgaard; for oxygen isotope analysis), and the melted water was quantified and sieved through a 10µm mesh for microscopy. Cysts of the ice-algae Polarella glacialis were found. A species of Protoperidinium, which has not previously been documented to be living in sea-ice, was found in large numbers. We isolated cells to PCR tubes for single DNA sequencing and lugol-fixed part of the samples for later electron microscopy for precise species determination. We will use the plankton-net samples for testing the presence of the species in the water column and fixed water samples (taken before filtration) for quantification. 2. To test the potential of sedimentary ancient DNA as a new proxy for Arctic sea-ice cover. Samples: This work will be based on several sets of samples: A. Water sampled during CTD casts at ca. 1 m depth (Surface), the depth of

the chlorophyll a maximum (DCM) and near the sediment surface (Bottom) (Fig. 14). At each full sampling station, and from each of these three depths, 10 liters of water were filtered on board through GF/F filters and immediately transferred to cryo-vials and frozen at -80°C.

B. Surface sediment sample from each full sampling station taken with a box-corer or Haps-corer and frozen at -80°C immediately after subsampling.

C. Sediment cores taken with a Rumohr corer and either frozen intact or sub-sampled and frozen on board (Fig. 15); from 5 stations.

D. Multinet plankton samples taken with two 20µm nets (11 casts in total) from respectively near-bottom to 30 meters and 30 meter to the surface (Fig. 16, Appendix 4). Each sample was split in two with one sample frozen at -80°C and the other fixed with lugol iodine; the frozen sample for DNA analysis and the fixed sample for microscopy.

Bottom water

Surface water

DCM water

Surface sediment

Sediment core

Fig. 13. Samples for testing environmental DNA will be derived from the water column and the sediments. Diagram by Marianne Ellegaard.

18

The frozen samples will be processed in collaboration with the Centre for Geogenetics at the University of Copenhagen and used to test the potential for assessing biodiversity in the water and sediment using methodologies for environmental DNA analyses, and to assess the rate of preservation of the DNA signals down through the water column and into the sediment archive (Fig. 13). The fixed samples will be used to compare the DNA sequences with the morphological species present at each depth. For the sediments, archived cores from each station will serve this purpose.

Fig. 14. Left: Water was collected during CTD casts from selected depths (surface, DCM, and bottom) and Right: immediately filtered through GF/F filters (10l per depth). A sub-sample of 250ml of water from each depth was Lugol’s fixed for taxonomic determination of the plankton after the cruise. Photos: Marianne Ellegaard (Left) and Karen Gariboldi (Right).

Fig. 16. The plankton multinet could be equipped with nets of 20μm mesh size for phytoplankton sampling. The “Phyto 4” net was kept open from near the bottom to 30m water-depth, and “Phyto 5” was open from 30m depth to the surface. Photo: Christof Pearce.

Fig. 15. To investigate the long-term response of indicator species to environmental changes, we have kept 5 Rumohr cores intact and sealed for isolating and germinating living resting cells of diatoms and dinoflagellates from dated sediment layers for time-series experiments. Other Rumohr cores were split and subsampled on board as shown here. Photo: Marianne Ellegaard.

19

Sea floor morphology: Shallow seismic acquisition By Katrine Juul Andresen, Lasse Nygaard Eriksen, Tove Nielsen and Tine L. Rasmussen Objectives The shallow seismic investigations on the NorthGreen2017 cruise served two purposes:

1) To investigate the geology of the surveyed area; i.e. map deep reflections, faults and folds, varying seafloor morphologies, sediment packages, mass transport complexes (MTCs) (e.g. slides and slumps), canyons etc.

2) To identify suitable locations for the sediment sampling program (Box/Haps, Rumohr and Gravity coring), i.e. find areas where soft sediments (mud) are present (preferable >5 m in thickness)

The main surveying was done during night time to allow for samples (water, nets and sediments) to be taken during day time. Instrument The subbottom profiler (SBP) instrument used for the shallow seismic surveying onboard RV Dana is of the type: Innomar SES-2000 Deep, Narrow-Beam Parametric Sub-Bottom Profiler. The instrument is hull-mounted centrally on the ship and associated with a motion sensor (MS) for recording the heave, pitch and roll variations (Fig. 17). Unfortunately, the motion sensor did not function for the NorthGreen2017 cruise, so no heave correction has been applied to the recorded data.

The SES-2000 Deep instrument is a parametric subbottom profiler system of the pinger type, with a fixed high-frequency (HF) component of 35 kHz, and a low-frequency (LF) range of 2-7 kHz. As the target area for the cruise was the NE Greenland Shelf (and the Young Sound) the majority of the surveying was carried out at water depths of 100-600 m in which the 4 kHz LF mode gave the best results. The ping-rate is semi-automatically set by the instrument and was typically 0.97-1.70 pps (pings per second) within the 300-600 m water depth range, up to ca. 3.6 pps for water depths around 150-200 m, and up to ca. 8-10 pps in the shallow Young Sound (0-100 m).

Methods The subbottom profiler system works by transmitting a high-frequency ping (electronic signal) which is reflected from the seafloor and subsurface layer boundaries and received back and recorded at the transducer (Fig. 18). The reflected ping is transformed into images (vertical sections/profiles) of the subsurface by utilizing the difference in arrival time from reflectors at varying depths. The Innomar® instrument records the data in .ses and .raw format (Fig. 19), which is converted to .segy format using the build-in SES-convert software. Both the HF and LF component of the recorded data is converted to .segy. No particular processing of the raw data was carried out onboard RV Dana, and heave-correction could as mentioned not be performed due to malfunctioning of the motion sensor. After conversion, the segy-files were loaded into Kingdom Suite (seismic interpretation software) (Fig. 20) and preliminarily interpreted.

20

Fig. 17. Permanently installed Innomar SES-2000 Deep subbottom profiler at RV Dana. Left: transceiver unit. Right top: transducer viewed from below. The transducer transmits and receives the signal (ping). Right bottom: view at the hull mounted (moon pool installation) transducer from above (below white deck). The motion sensor (unfortunately not working) recording heave, pitch and roll variations for the SES-200 Deep instrument can be seen on top of the white deck. Photos: Katrine Juul Andresen (left) and Christian Petersen (right, both).

Fig. 18. Principle of seismic reflection used in subbottom profiling. Reflections from the deeper geological layers will arrive later (i.e. longer two-way travel times (TWT)) than reflections from the shallower layers. The difference in arrival time can be processed into images (vertical sections/profiles) of the subsurface. Source: Ref. 20.

Data The Innomar SES-2000 Deep subbottom profiler delivers ultra high-resolution seismic data optimized for mapping the shallowest subsurface. Depending on the geology of the investigated areas and the water depths, the penetration depth is typically around 15-20 m. In Young Sound the depth of penetration reached ca. 50 m.

21

Concerning seismic resolution, an average velocity of 2000 m/s for the sediments gives a dominant wavelength of 0.5 m (using a dominant frequency of 4 kHz) which in turn gives a vertical resolution around 25 cm (estimated here as half the dominating wavelength). Hence, we should be able to fully resolve layers that are above 25 cm in thickness. Compared with other types of reflection seismic surveying, this is a very high resolution. For airgun seismics, the typical resolution is around 10-50 m with penetration depths up to ca. 2-4 km (single airgun). For sparker sources the resolution is in the order of ca. 1-5 m with penetrations up to ca. 500 m (depending on the instrument type).

Fig. 19. Example of raw data recording from the SES-2000 Deep instrument at a section from Station 8 gravity core position during the NorthGreen2017 expedition. Settings for the data recording are adjusted in the panel to the left.

Fig. 20. Corresponding image of the deposits from Figure 19 in Kingdom Suite, where the reflections appear more well-defined. Note differences in vertical and horizontal scale (ca. 10 x vertical exaggeration). The LF component showed more continuous noise within the water column and sediments (of frequencies between 1.5-5 kHz) than the HF component (see Fig. 19). Several noise-tests were performed to check whether this noise could be reduced. The tests included switching off other acoustic instruments onboard RV Dana, such as the single-beam echosounder (scientific echosounder), the sonar, and the ADCP (Acoustic Doppler Current Profiler). No effects were recorded while turning off these devices. The noise-level was furthermore not affected by the speed of the vessel, but may still be related to constant engine noise throughout the cruise. Alternatively, the noise may be generated from poor maintenance and little use of the SES-2000 Deep instrument itself. The subbottom profiler has been installed on RV Dana since 2012 but has not been used regularly prior to the NorthGreen2017

22

cruise. Algae growth (or similar) on the transducer and weakening of the mounting structure may also generate unwanted noise. Preliminary results A total of ca. 2200 km of shallow seismic data were acquired during the research cruise. Three dredge positions and 16 stations for sediment sampling were identified from the surveying. The data cover a wide range of different geological provinces across the NE Greenland Shelf but can roughly be subdivided into deep troughs and fjords (formed by glacial erosion), inter-trough areas, and basement highs, which also appear to be affected by glaciers. In nearly all areas, a thin cover (1-3 m) of most likely Holocene mud drapes the varying structures. Larger sedimentary basins (with estimated mud/clay thickness up to 15-20 m, e.g. Fig. 20) were only encountered in a few places on the shelf. Within the Young Sound fjord, the thickest sedimentary packages were observed. Varying seafloor morphologies have been recognized such as blocky (faulted?) seafloor, rugged seafloor (MTCs?), iceberg ploughmarks, basement outcrops and flat seafloor related to sedimentary basins. Similarly, the reflections below the seafloor show varying characteristics such as parallel high-amplitude continuous reflections and low-amplitude discontinuous chaotic reflections. Further analysis After the cruise, the seismic data will be processed in order to optimize the imaging of the subsurface. Processing of the raw Innomar® subbottom profiler data, will consist of noise reduction in both LF and HF channels. An attempt will be made to correct for the missing heave, pitch and roll. After processing, the data will be re-loaded in a seismic interpretation software, where further analyses and interpretation of the seismic data will be carried out in order to identify and differentiate varying seafloor morphologies and substrates for the NE Greenland Shelf. The seismic interpretation will utilize standard interpretation methods for structural and stratigraphic interpretation, and the seafloor and deep reflections will be mapped. If possible, seismic amplitude and attribute analysis will be utilized in further analyses.

Because the Innomar® data were recorded mainly during transit, the interpretation of the data will most likely focus on a broader and more general description of the area instead of specific areas. The Young Sound and Tyroler Fjord could represent a potential focus area, since good seismic coverage was obtained here and multibeam data from previous cruises are available. Information from the Gravity and Rumohr cores and the dredging profiles will be integrated with the seismic analyses in order to constrain lithologies and selected morphologies.

Sediments By Christof Pearce, Karen Gariboldi, Camille Brice, Lasse Nygaard Eriksen, Cynthia LeDuc, Anders Møller Mathiasen and David Wangner Abbreviations R: Rumohr H: Haps ITRAX: XRF Core scanner (at Dept. of Geoscience, Aarhus University) MESR: Marianne Ellegaard (KU) and Sofia Ribeiro (GEUS) AU Geoscience/ AU Geo: Marit-Solveig Seidenkrantz and Christof Pearce Geomicrobio: Hans Røy and Caroline Scholze

23

Sediment sampling equipment Van Veen Grab. The most simple and fast way to retrieve a big sample from the sediment surface is the van Veen Grab (Fig. 21). This device was used at only one station during the cruise. A simple closing mechanism grabs the upper ~30 cm of the surface sediments. Box corer / Haps core. A box corer is capable of taking a relatively large area of undisturbed surface sediments. Box cores comes in all sizes. The large box corer, hereafter the box corer was only deployed at Station 1. The smaller box core, hereafter the Haps corer, was used at all other sediment stations. The “Haps” is a small box corer meant

to sample the very first centimetres (ca. 30 cm) of the sediment column and the water/sediment interface. The Haps corer consists of a metallic cylinder which is deployed in the sea water by means of a wire. The cylinder is installed on a metallic frame and it penetrates the sea bottom thanks to the weight of its structure. As it reaches the sea bottom, the wire loses tension, triggering a blade that close the base of the cylinder, allowing the recovery of the sediments. The Haps corer was mainly used to sample the first two centimetres (0-2 cm) of the sediments column, which can be used to study different geological and biological aspects of the very recent past. Water from the water/sediment interface was removed by means of syringes; sediments were then collected by means of a spatula. Samples for microplastic analysis were collected by means of a cylinder with a known volume. Three plastic tubes (diameter = 4 cm, length = 25cm) were used as micro liner to subsample the entire sediment column collected by the Haps corer; to facilitate this procedure, a pump was used to create a very low vacuum within the tubes. These tubes will be used to study the living depth of benthic foraminifera. A list of all the samples collected at each station and of the different methods that were used to store them, is given in Table 1, together with the name of the person who required the

sample (persons in italics did not attend the cruise). Normally, three Haps cores were collected at each Station and these were sufficient to recover all sample listed in Table 1. Occasionally extra Haps cores were collected for comparison studies (samples for Christof Pearce) or for microbiologically purposes (sample for Caroline Scholze).

Fig. 21. Van Veen grab full of sediment coming on deck. Photo: Christof Pearce.

Fig. 22. Deployment of box corer. Photo: Christof Pearce.

24

Table 1. Sampling scheme for sub-samples of the Box/Haps cores.

What Short name Depth Sample size

type Container Storage Who

Living benthic foraminfera TUBE-1 Tube 3 microtubes Tube Freezer, -20 Karen Gariboldi (for Caterina

Morigi), Pisa U., Italy Living benthic foraminfera TUBE-2 Tube 3 microtubes Tube Freezer, -20 Karen Gariboldi (for Caterina

Morigi), Pisa U., Italy Living benthic foraminfera TUBE-3 Tube 3 microtubes Tube Freezer, -20 Karen Gariboldi (for Caterina

Morigi), Pisa U., Italy

Microplastic MP Top 1 cm 5 cm diameter Metal tube Cool room Karen Gariboldi (for Caterina

Morigi), Pisa U., Italy

DNA DNA Top 2 cm 15 ml Whirl-pak bag Freezer, -80 Sofia Ribeiro & Marianne Ellegaard, GEUS

Alkenones ALK Top 2 cm 5-8 g wet sed. Whirl-pak bag Freezer, -20 Ralph Schneider, Kiel U, Germany

IP25 and other biomarkers IP25 Top 2 cm 10 ml Whirl-pak bag Freezer, -20 Christof Pearce, Geoscience, AU

Metal/Ca Mg/Ca Top 2 cm 10 ml. Bag Cool room Marit-Solveig Seidenkrantz, Geoscience, AU

C, N, 13Corg, 210 Pb etc CN Top 2 cm 5 ml Bag Cool room Anne de Vernal, Geotop, UQAM,

Canada

Grain size, TOC Grain Top 2 cm 30 ml Bag Cool room Marit-Solveig Seidenkrantz & Christof Pearce, Geoscience, AU

XRD XRD Top 2 cm 15 ml Bag Cool room Marit-Solveig Seidenkrantz & Christof Pearce, Geoscience, AU

Rock-Eval RE Top 2 cm 1 ml Bag Cool room Marit-Solveig Seidenkrantz, Geoscience, AU

Diatoms DIA-1 Top 2 cm 2 ml Bag Cool room Diana Krawczyk, Greenland

Diatoms DIA-2 Top 2 cm 2 ml Bag Cool room Hui Jiang, ECNU, China

Diatoms DIA-3 Top 2 cm 2 ml Bag Cool room Arto Miettinen, NPI, Tromsø, Norway

Diatoms DIA-4 Top 2 cm 2 ml Bag Cool room Nina Lundholm, Natural History Museum of Denmark (SNM)

Dinoflagellates DINO-1 Top 2 cm 15 ml Bag Cool room Anne de Vernal, GEOTOP, UQAM, Canada

Dinoflagellates DINO-2 Very top 15 ml Bag Cool room Sofia Ribeiro & Marianne Ellegaard, GEUS

Benthic foraminferal BF Top 2 cm 2 ml Bag Freezer Karen Gariboldi (for Caterina

Morigi), Pisa U, Italy. Planktonic foraminfera PF Top 2 cm 5-10 ml Bag Cool room Siri Ofstad, UiT, Tromsø, Norway

PAH PAH Top 2 cm 60 gram Rilsan bag Cool room Anders Mosbech, Bioscience, AU

Sediment rest REST Top 2 cm Everything left Bag Cool room Marit-Solveig Seidenkrantz &

Christof Pearce, Geoscience, AU

25

Rumohr Corer. A Rumohr core (Fig. 23) is a 1 to 2 meters long, and ~8 cm wide sediment core. Sediments are collected in a PVC liner attached to a gravity device, and kept in the liner by a closing

valve on top of the liner, causing reduced pressure. Rumohr cores are often used in association with Gravity cores to complete sediment record as they can preserve the surface. At every station, a core in good condition is closed and preserved as an archive record, for e.g. XRF core scanning. Some of the cores are subsampled onboard at every 0.5 cm for the first 100 cm and every 1 cm onward, for multiples analysis such as DNA, isotopes, metal trace, sedimentology, micro-paleontology, micro-biology, etc. Gravity Corer. The Gravity corer was set up to collect cores of up to 6 m length (the longest core retrieved during NorthGreen2017 was 5.8 m long); once a 9m core was tested without. Gravity cores are therefore capable of taking samples dating further back than those taken using the Rumohr corer. The Gravity corer consists of a long metal outer tube, with a plate and some weights in the top (Fig. 24a). The plate prevents the

top of the corer from penetrating the sediments, thus preventing the loss of surface sediment through the top of the corer. For each deployment the corer was loaded with a plastic liner (PVC tube) that served as sediment container. Furthermore a core-catcher was added to the bottom of the metal casing. (Figure 24b). The core-catcher prevented the collected sediments in the liner from falling out of the tube after sampling. When deployed, the corer was lifted from the deck and over the side of the ship with a regular crane. The corer was then attached to a winch through a pivoting arm, ensuring sufficient spacing between the corer and the ships side. The corer was subsequently lowered through the water until penetrating the seafloor, and afterwards brought back on deck. On deck the core-catcher was detached from the rest of the corer, and the liner containing sediment was cut into sections of 1 m each. Each section was capped and finally stored in a cooling room. The core-catcher is responsible for a major disadvantage of the Gravity corer, as it disturbs and compresses the surface sediment upon penetrating the seafloor. This problem is difficult to avoid, as the core-catcher is a necessary part of the corer. By also taking samples using the Rumohr corer, the problem was minimized as this method preserves the surface sediments much better.

Figure 24. a) The Gravity corer in its full length being deployed. b) The core-catcher right after deployment still containing fresh sediment. Photos: Christof Pearce.

Fig. 23. Rumohr corer full of sediments. Photo: Christof Pearce.

26

Dredge. To determine local basement rocks and outcrops, samples were recovered with the help of a dredge (Figs. 25, 26). Basement rock can be distinguished from drop stones by sharp edges and the lack of rounding. The determination of the basement helps to precise the origin of icebergs, which are transported southwards along the Greenlandic coast and release sediment while melting. The dredge consists of a grabbing box with a metal net attached to it and is usually pulled along the seafloor collecting coarse material like drop stones or pieces of outcrops. In case the dredge gets stuck on the seafloor and the main wire rips, an additional safety wire is attached to the back of the net to recover the dredge. Best sample recovery is usually reached, pulling the dredge up a slope. Sample sites were chosen based on previous collected Innomar® data. Besides the morphology of the seafloor, they were expected to have exposed pre-quaternary basement rock exposed on the surface. After the net was emptied on deck, rock samples were selected and stored in sample bags for further analyses.

Fig. 26. Drawing of the dredge with the main wire in the front, holding 4.75 t and the safety wire holding 9.5 t attached to the back of the net (©Helmut Kawohl).

Fig. 25. The dredge, used on the NorthGreen2017 expedition. Photo by the crew of RV Dana

27

Results of sediment sampling – Summary per station A total of 84 (Rumohr and Gravity, Appendix 2) sediment cores as well as 48 surface sediment and dredge samples (Appendix 3) were collected successfully from 15 different stations (Appendix 2-4). At the remaining stations only CTD measurements, water sampling or plankton net casts were carried out (Appendix 4). Station 1 Started with 1 box core (Event 9B). The bucket and lid did not fit together, so it did not close well. After a struggle the bucket was released and the sediments were fine. But this was the first and last time we used this device. Hereafter all surface sediments were taken with Haps samplers (smaller box core). 7 Rumohr cores

- 3 for AU Geoscience o 10R archive for ITRAX etc o 12R o 14R sliced in 0.5cm and kept in fridge

- 2 for MESR o 11R intact in fridge o 15R intact in freezer

- 2 for Geomicrobio (17R and 18R, both consumed) 1 Gravity core (150 cm), cut in 2 sections. Kept intact. Station 3 7 Rumohr cores

- 3 for AU Geoscience o 31R o 33R sliced in 0.5cm and kept in fridge o 36R archive for ITRAX etc

- 2 for MESR o 30R intact in fridge o 32R intact in freezer

- 2 for Geomicrobio (consumed) 1 Gravity core 39G (320 cm), cut in 4 sections. Kept intact. 4 Haps cores

- 36H, 40H, 41H sampled for AU geo - 37H taken for geomicrobio (Caroline)

Station 5 Good surface samples, but nothing more. Started with 3 Haps (48H, 49H, 50H), all sampled for AU Geo. 1 Gravity core (51G). Only 30 cm recovery, saved in 1 short section. Gravel in the core catcher 1 Rumohr (52R). 30 cm recovery and then liner broke. Looks like the same hard gravel layer. Station 7 7 Rumohr cores

- 3 for AU Geoscience o 68R o 69R sliced in 0.5cm and kept in fridge

28

o 70R archive for ITRAX etc - 2 for MESR

o 71R intact in fridge o 72R intact in fridge

- 1 for Geomicrobio (79R, consumed) 2 Gravity cores 73G and 80G. 4 Haps cores

- 3 sampled for AU geo (74H, 75H, 77H) - 1 taken for geomicrobio (76H)

Station 8 This station has 2 sub-stations. Two nice sites were found within close proximity, both with thick packets of sediments. First one with 3 Rumohr (89R, 90R, 91R), 1 Gravity (92R), 3 Haps (93H, 94H, 95H). Second with 1 gravity (96G), 2 Rumohr (97R, 98R). All for AU Geoscience. Station 10 Again 2 sub-stations. First with poor recovery, much better at second site. First with 2 Rumohr (108R, 109R), 1 Gravity (110G) of 70 cm with gravel in the core catcher, 3 Haps (111H, 112H, 113H). Second site: Seismics indicated thick section of sediment with an additional reflector on top of reflector seen at seismic site #108. 3 Rumohr (116R, 120R, 121R), 1 Gravity (117G). All for AU Geo Station 12 3 Rumohr (132R, 133R, 134R), 1 Gravity (135G), 4 Haps (136H, 137H, 138H, 139H). All to AU Geo Station 13 Chosen for big deeper area (ca 400 m) near the shelf break, but the seismics indicated very rough and pointy terrain. Very little sediments in the entire region, but one site was chosen based on a shallow drape of a few meters of sediments. 4 Rumohr (148R, 149R, 150R, 151R), 1 Gravity (152G) and 3 Haps (153H, 154H, 155H). Not more than 2 m recovery. Station 14 This station was chosen for a mooring to be placed out outside Young Sound. A seismic survey indicated thick sediments just east of the mooring. That site is chosen for the full station 14. Surface sediments from this station were much coarser than in the other stations (up to pebbles). Tube worms and worms were frequent. We took 1 extra Haps (174H) for Christof Pearce here (intercomparison study). Several Rumohrs failed, but we got 5 good ones. 5 Rumohr cores:

- 3 for AU Geoscience o 166R o 167R sliced in 0.5cm and kept in fridge o 173R archive for ITRAX etc

- 2 for MESR o 168R intact in fridge o 172R intact in fridge

1 Gravity core 171G (420 cm), cut in 5 sections. Kept intact.

29

4 Haps cores - 3 sampled for AU geo (175H, 176H, 177H) - 1 extra for Christof Pearce – Intercomparison project (174H)

Station 15 Return to station with thick package (identified through Innomar® investigation). Quick station, only sediments and 1 CTD. The aim was to capture sediment sequence from the SIRIUS Polynya. This station is in the very southern part. 180G: 350 cm Gravity core 2 Rumohr cores: 1 sliced in freezer (182R), 1 intact as archive (181R). Station 16 In Young Sound now, spirits are high. Lot of slicing going on. 4 scientists (Siri, Cynthia, Camille, Mads = birthday) left for a tour to SIRIUS at Daneborg. Many Rumohr cores taken here, some failed. 2 for AU Geoscience (191R, 201R) 2 for MESR (192R, 193R) 2 for Geomicrobio (195R, 201R) Longest Rumohr was 185 cm (195R, used for Geomicrobio), but the Gravity core (203G) only retrieved 160 cm. This station was revisited the day after to take 1 extra Haps that was missing (246H for geomicrobiology). Rumohr 181 was sliced and bagged, but accidentally labelled as 191R. The bigger bags have corrected labels, but not the small individual samples. Station 17 Simple short station included to sample mollusks (Christof Pearce). 2 Van Veen Grabs (211B, 212B). Completely sieved for mollusks. Living specimens are saved in ethanol. Dead specimens are dried. Station 18 Sediment only station. 1 Gravity (213G), 3 Rumohr (214R, 215R, 216R). Station 19 Full Rumohr core program (MESR, AU Geo, Geomicrobio). Several failed, 6 were good (226R, 227R, 228R, 230R, 231R, 232R). 370 cm Gravity core (235G). Station 21 Sediment only station. 1 Gravity core 245G (360 cm), 2 Rumohr (243R intact in fridge, 244R sliced and frozen). Station 22 230 cm Gravity core 252G and 2 Rumohr cores 253R and 256R.

30

Geomicrobiology By Caroline Scholze and Hans Røy Objectives The purpose of this subproject was to look at temperature adaptation of microbial communities in sediments that have been subject to permanently cold conditions for the last thousands of years and which have not been influenced by any input from warm current during this time. Compared to sites in the Arctic that are influenced by warmer bottom currents as for example the West Coast of Svalbard, permanently cold East Greenland sediments should show a distinctly lower temperature optimum of the in situ community. In fact, the temperature optimum of the bacteria living in Young Sound sediments are expected to be the lowest recorded so far. Methods Subsamples for geochemical analysis were taken at station 1, 3, 7, 16 and 19. Sediments were subsampled from Haps cores and Rumohr cores. Pore water was extruded from Rumohr cores at 2.5, 5 cm and from 10 cm on downwards every 10 cm until the bottom of the core liner. Solid phase samples were taken from a second Rumohr core at each station directly at the sediment-water interface, at 2.5, 5 cm and from 10 cm on downwards every 10 cm until the bottom of the core liner (see also sampling scheme Table 2). Solid Phase. Sediment was sampled for CH4 concentrations, sulfate reduction rates (SRR) and density measurements and DNA. CH4 samples were preserved in saturated saltwater in 20 mL glass vials, shaken and stored upside down at -20°C. In situ sulfate reduction rates are measured with the radio tracer method. Therefore, sediment subsamples were incubated with 35S-SO4

2- for 12 hours at 2°C during the cruise. After the incubation sampled transferred into 5 mL of 20% Zink-acetate to stop all biological activity and preserve the sulfide formed. A known volume of sediment was taken from each sampling depth to determine the density and the porosity of the sediment. DNA samples were subsampled into sterile cut-off syringes (Fig. 27) in duplicate at every sampling depth and been frozen. Pore water. Pore water was sampled using Rhizon soil moisture samplers (Rhizosphere Research Products, Wageningen, Netherlands) inserted through 3.8 mm drilled holes in the Rumohr core liner. Samples were prepared for measuring Fe(II), HS-, SO4

2-, NH4+, DIC and Kation concentrations (Fig. 28). Samples of 500 µL for Fe(II) analysis were directly transferred into 15 mL Falcon tubes prefilled with 500 µL of 6 M HCl and stored at 4°C. For sulfide concentrations 500 µL were transferred into 15 mL Falcon tubes prefilled with 1 mL of 20% Zink-acetate and stored at -20°C. For SO4

2- and NH4+ concentrations 500 µL of sample have been pipetted into one Eppendorf tube each. Sulfate samples were stored at

Fig. 28. Pore water subsampling from a predrilled Rumohr core into 20 mL syringes through Rhizon filters by applying vacuum. Photo: C. Scholze.

Fig. 27. Sampling port and syringe for subsampling of solid material. The Rumohr lot is extruded into the sampling port and all samples can be taken at the exact same depth. Photo by C. Scholze.

31

4°C, while ammonium samples were frozen at -20°C. 2 mL of sample have been pipetted into a 2 mL glass vial and stored at 4°C. The leftover sample has been transferred to a 10 mL glass vial for kation analysis and stored at 4°C. Temperature Gradient Experiment Samples have been taken for a laboratory experiment on the influence of temperature exposure. For this purpose, the uppermost 15 cm of Haps cores taken at station 3, 7, 16 and 19 have been subsampled into gastight bags (Fig. 29). Additionally, a deeper sample was taken from the bottom part of Rumohr

lots covering at least 10 cm depth intervals at the same stations. All samples have been kept anoxically and at 2°C. Preliminary Results. Five stations have been sampled for Geomicrobiology. Pore water and solid phase samples have been taken from the first meter of Station 1 and 3. At Station 7, 16 and 19 the uppermost 1.6 m were subsampled for geochemical analysis. From Station 3, 7, 16 and 19 the uppermost 15 cm have been subsampled for temperature gradient experiments in the laboratory in Aarhus. Additionally, 140-150 cm, 150-160 cm and below 160 cm have been subsampled for temperature gradient experiments

in the laboratory at station 16 and 19. From Station 1 the uppermost 5 cm, 45-55 cm and 75-85 cm from a Rumohr core have been subsampled for the temperature experiment. All samples have been taken according to the sampling scheme and process described in the method section.

Table 2. Scheme for sampling of geochemical parameters at Stations 1, 3, 7, 16 and 19

DEPTH SOLID PHASE SAMPLES POREWATER SAMPLES

0 2 x DNA SRR Porosity Fe(II) HS- SO42- NH4+ DIC Kations 2.5 2 x DNA SRR Porosity Fe(II) HS- SO42- NH4+ DIC Kations 5 2 x DNA SRR Porosity Fe(II) HS- SO42- NH4+ DIC Kations

10 2 x DNA SRR Porosity Fe(II) HS- SO42- NH4+ DIC Kations 15 2 x DNA SRR Porosity Fe(II) HS- SO42- NH4+ DIC Kations 20 2 x DNA SRR Porosity CH4 Fe(II) HS- SO42- NH4+ DIC Kations 30 SRR Porosity CH4 Fe(II) HS- SO42- NH4+ DIC Kations 40 2 x DNA SRR Porosity CH4 Fe(II) HS- SO42- NH4+ DIC Kations 50 SRR Porosity CH4 Fe(II) HS- SO42- NH4+ DIC Kations 60 2 x DNA SRR Porosity CH4 Fe(II) HS- SO42- NH4+ DIC Kations 70 SRR Porosity CH4 Fe(II) HS- SO42- NH4+ DIC Kations 80 2 x DNA SRR Porosity CH4 Fe(II) HS- SO42- NH4+ DIC Kations 90 SRR Porosity CH4 Fe(II) HS- SO42- NH4+ DIC Kations

100 SRR Porosity CH4 Fe(II) HS- SO42- NH4+ DIC Kations 110 SRR Porosity CH4 Fe(II) HS- SO42- NH4+ DIC Kations 120 2 x DNA SRR Porosity CH4 Fe(II) HS- SO42- NH4+ DIC Kations 130 SRR Porosity CH4 Fe(II) HS- SO42- NH4+ DIC Kations 140 2 x DNA SRR Porosity CH4 Fe(II) HS- SO42- NH4+ DIC Kations 150 2 x DNA SRR Porosity CH4 Fe(II) HS- SO42- NH4+ DIC Kations 160 2 x DNA SRR Porosity CH4

Fig. 29. Subsamples in gastight bags with a temperature logger stored in the cold room. Photo by C. Scholze.

32

Microplastics in deep sea sediments By Caterina Morigi and Karen Gariboldi

Objectives

The main aim of this project is the identification of the microplastic contamination of the Greenland deep sea. For that purpose, surface sediments were sampled during the cruise. Plastic is one of the most distributed and abundant contaminant in the sea and its distribution is almost global. In particular, microplastics (63-500 μm) have already been recorded in polar remote area, both in the water column and in the ice. The Greenland Sea is still one of the most remote and unpolluted areas. This project aims at testing the presence, the abundance and composition of microplastics in the East Greenland shelf region. Furthermore, investigations on spatial differentiation of abundance and composition with depth will be conducted. The results of this project will help to clarify the contribution of vertical propagation for the general spatio-temporal distribution of marine microplastics. Methods To analyse the distribution of microplastic in surface and near-surface sediments, sediments were sampled using the box corer and Haps. At each “sediment station”, microplastic was collected from one single Box/Haps corer by means of a hollow metal cylinder. This instrument has a diameter of 5 cm and is marked on its side with a line at 1 cm above its rim. The cylinder was pushed into the surface sediments until this line, allowing the collection of a known volume of sediment. Samples were stored at +4°C. In total, we collected 11 sediment samples for microplastic analysis. Sample preparation in the laboratory at University of Pisa, Italy, will be conducted through a plastic-preserving enzymatic-oxidative maceration with a subsequent density separation. The separation of the microplastic will be performed with a stereomicroscope and the determination of the type of polymer will be performed using the Raman spectroscopy analysis.

Living and recent benthic foraminifera By Caterina Morigi and Karen Gariboldi

Objectives and general procedures The comprehension of one of the least known and most extreme ecosystems in these permanently cold and presumably nutrient-limited marine sediments is a common scientific goal. We will study the response of the benthic meiofaunal communities to this extreme ecosystem. Data on living foraminifera is generally very poor and biodiversity is likely underestimated. Foraminifera are eukaryotic unicellular organisms which, coupled with the study of microbial communities can give us some important information on trophic ecosystem dynamics.

Methods Three replicate sub-cores (internal diameter of liner 4 cm, 25 cm length) for ecological analyses on benthic foraminifera and one surface sediment sample (0-2 cm of depth, 2ml) for analyses Mg/Ca and (possibly) DNA were collected at every “sediment station” from one/two Box/Haps corers. All these samples were stored at -27°. Tubes were pushed into the sediment with the help of a hand-made-low vacuum-pump made by Hans Røy (Fig. 30).

In total, we collected 11 sediments samples for DNA analysis and 36 tubes for ecological analysis.

33

Content of the analyses

1. Faunal analyses of living benthic Foraminifera including soft-shelled taxa (i.e., allogromiids sensu lato) to estimate their biodiversity and their ecological requirements. Most of the allogromiid taxa are still undescribed and the benthic foraminiferal fauna could represent in this potentially extreme environment a useful tool to evaluate the response of biota to stressed conditions.

2. Shell ultrastructure analyses on selected species of calcareous foraminifera to evaluate how and if biomineralization is influenced by environmental parameters (i.e., oxygen, T, pH, etc.). Analyses on mineral and organic components of the shell: Such organic molecular and inorganic geochemical coupling approach is innovative. It will provide a better understanding of the incorporation mechanisms or/and the chemical proxies (trace elements as Mg/Ca and isotopes as δ18O) in the calcite foraminiferal tests. Finally coupling geochemical and biological perspectives on foraminifera will enhance interpretation of the proxies used for environmental and climatic reconstructions and improve future interpretation efforts in paleoclimatology.

Fig. 30. Hand-made pump made by Hans Røy. A. Hand-made pump. B and C. Details. D. Camille Brice pushing the tubes into the sediment using the hand-made pump. Photos by Karen Gariboldi.

34

Seabird and marine mammal survey in the Greenland Sea By Jarl Regner Andersen As part of the NorthGreen2017 expedition, a survey of seabird and marine mammals was undertaken. The Greenland waters are important for many seabird and marine mammal populations and some marine mammal and seabird species are important resources for Greenlanders. However, the knowledge on seabird and marine mammal distribution and abundance in the Greenland Sea is sparse and as oil activities may impact on marine mammals and seabirds, more knowledge is needed for Environmental Impact Assessment (EIA) work and planning. During the Dana cruise, data was systematically collected on abundance and distribution of seabirds and marine mammals according to the Manual for Seabirds and Marine Mammal Survey on Seismic Vessels in Greenland, 4th edition, April 2015, Scientific Report from DCE, Danish Centre for Environmental Environment and Energy, Aarhus University. The following species were observed during the cruise: • Birds:

o Fulmar Fulmarus glacialis o Long-tailed Duck Clangula hyemalis o Gyrfalcon Falco rusticolis o Longtailed Skua Stercorarius longicaudus o Arctic Skua Stercorarius parasiticus o Pomarine Skua Stercorarius pomarinus o Glaucous Gull Larus hyperboreus o Kittiwake Rissa tridactyla o Ivory Gull Pagophilia eburnean o Arctic Tern Sterna paradise o Thick-billed Murre Uria lomvia o Black guillemot Cepphus grille o Atlantic Puffin Fractergula arctica o Little Auk Alle alle o Raven Corvus corax o Snow bunting Plectrophenax nivalis

• Mammals: o Polar Bear Ursus maritimus o Fin Whale Balanoptera physalus o Whales not identified to species Ceteacea sp. o Muskox Ovibus moshatus

35

Examples of future analyses • The sediment cores collected during the cruise will, among others, be studied for

sedimentology (grain size, lithology, trace elements and magnetic susceptibility), micropalaeontology (foraminiferal, dinoflagellate cyst and diatom communities) carried out at the Department of Geoscience, Aarhus University in collaboration with national and international partners.

• Based on the results from solid phase and pore water analysis, carried out in the laboratories in the Center for Geomicrobiology, we will gain insight into the function of the microbial communities buried in Arctic sediments.

• Analyses on surface sediments carried out in the laboratories of the Department of Earth Sciences (Pisa University) will give insights of the pollution of the Greenland Sea by microplastics.

• Hydrological measurements and chemical analyses of water samples will provide information of the source of the surface and subsurface waters along the NE Greenland coast, especially the route of the Atlantic Water and the distribution of local water vs. East Greenland Current Water.

• Phyto and Zooplankton samples will be analysed in detail to provide information on the biota and food web and will provide the background information needed for interpretation of palaeoenvironmental and palaeoclimatic conditions based on the fossil assemblages of the sediment cores.

• Data on biological oceanography and seabirds will contribute to the Strategic Environmental Study Plan for Northeast Greenland.

• Parts of this work will be carried out by MSc and PhD students as part of their thesis projects.

Educational perspective A total of eight students and early stage researchers from Denmark, Canada and Italy participated in the expedition, thus giving it a very significant educational impact. In addition, four of the students from Aarhus University will continue studying the material from the cruise for their projects. Additional PhD, MSc and BSc are planned based on the material and data collected during the expedition.

Post cruise meeting The first interdisciplinary post-cruise workshop will take place on March 22, 2018, at the Department of Geoscience, Aarhus University.

R/V Dana in Young Sound, NE Greenland. (Photo: Claus Persson, Captain of Dana, DTU-AQUA).

36

References [1] Quadfasel, D., Gascard,J.-C., Koltermann, K.-P., 1987. Large-scale oceanography in Fram Strait

during the 1984 Marginal Ice Zone Experiment. Journal of Geophysical Research, Oceans 92 ( C7), 6719–6728. DOI: 10.1029/JC092iC07p06719.

[2] Schauer, U., Fahrbach, E., Osterhus, S., Rohardt, G. 2004. Arctic warming through the Fram Strait: Oceanic heat transport from 3 years of measurements. Journal of Geophysical Research: Oceans 109 (C6), 2156-2202. DOI: 10.1029/2003JC001823.

[3] Müller J, Stein R, 2014. High-resolution record of late glacial and deglacial sea ice changes inFram Strait corroborates ice–ocean interactions during abrupt climate shifts. Earth and Planetary Science Letters 403, 446–455. Doi: 10.1016/j.epsl.2014.07.016.

[4] National Snow and Ice Data Centre, USA. http://nsidc.org. [5] Stroeve J, Holland MM, Meier W, Scambos T, Serreze M, 2007. Arctic sea ice decline: Faster

than forecast. Geophysical Research Letters 34 (9), DOI: 10.1029/2007GL029703. [6] Kinnard C, Zdanowicz CM, Fisher DA, Isaksson E, de Vernal A, Thompson, L, 2011.

Reconstructed ice cover changes in the Arctic during the past millennium. Nature 479, 509-512. [7] Funder S, Gosse H, Jepsen HF, Kaas E, Kjær KH, Korsgaard NJ, Larsen NK, Linderson H, Lyså

A, Möller P, Olsen J, Willerslev E. 2011. A 10,000-year record of Arctic Ocean sea ice variability - View from the beach. Science 333, 747-750.

[8] Seidenkrantz, M-S, de Vernal, A, Goosse, H, Solignac, S, Van Nieuwenhove, N, Macias-Fauria, M, Klein, F, Pearce, C, Belt, S, Caissie, B, Cronin, TM, Stein, RH, Sha, L, DeNinno, LH 2014. Northern Hemisphere sea-ice cover during the Holocene – proxy data reconstruction and modelling. American Geophysical Union, Fall Meeting, San Francisco 14-19 December 2014.

[9] Holland D M, Thomas RH, de Young B, Ribergaard MH, Lyberth B, 2008. Acceleration of Jakobshavn Isbræ triggered by warm subsurface ocean waters, Nature Geoscience 1(10), 659–664.

[10] Straneo F, Heimbach P, 2013. North Atlantic warming and the retreat of Greenland’s outlet glaciers. Nature 504, 36-43.

[11] Amundson, J. M. et al. Ice mélange dynamics and implications for terminus stability, Jakobshavn Isbræ, Greenland. J. Geophys. Res. 115, F01005 (2010).

[12] Deser C, Walsh JE, Timlin MS, 2000. Arctic Sea Ice Variability in the Context of Recent Atmospheric Circulation Trends. Journal of Climate 13 (3), 617–633.

[13] Bamber J, Van Den Broeke M, Ettema J, Lenaerts J, Rignot E, 2012. Recent large increases in freshwater fluxes from Greenland into the North Atlantic. Geophysical Research Letters 39, 8–11.

[14] Jakobsson, M. 2014. Arctic Ocean glacial history. Quaternary Science Reviews, 92, 40-67. [15] Arndt, J. E., W. Jokat, B. Dorschel, R. Myklebust, J. A. Dowdeswell, J. Evans (2015), A new

bathymetry of the Northeast Greenland continental shelf: Constraints on glacial and other processes, Geochem. Geophys. Geosyst., 16, 3733–3753, doi:10.1002/2015GC005931.

[16] Hirche H-J, Hagen W, Mumm N, Richter C, 1994. The Northeast Water polynya, Greenland Sea. Polar Biology 14, 491-503.

[17] Deming JW, Fortier L, Fukuchi M, 2002. The International North Water Polynya Study (NOW): An Overview. Deep-Sea Research Part II 49 (22-23), 4887-4892.

[18] GEBCO The General Bathymetric Chart of the Oceans, 2017: http://www.gebco.net/ [19] Arndt, J E, Jokat, W, Dorschel B, Myklebust R, Dowdeswell JA, Evans J, 2015. A new

bathymetry of the Northeast Greenland continental shelf: Constraints on glacial and other processes, Geochem. Geophys. Geosyst. 16, 3733–3753, doi:10.1002/2015GC005931.

[20] Stoker, Martyn S., Jack B. Pheasant, and Heiner Josenhans. "Seismic methods and interpretation." Glaciated Continental Margins. Springer, Dordrecht, 1997. 9-26.

37

Appendix 1. Samples collected for sea-ice proxy development

Station Activity Date Source Instrument Sample holder Water depth (m) Treatment

1 1 13/09/17 Water (10L) CTD/bottles Filter in cryotube bottom (315m) Frozen -80 °C

1 4 13/09/17 Water (10L) CTD/bottles Filter in cryotube 1m Frozen -80 °C

1 4 13/09/17 Water (10L) CTD/bottles Filter in cryotube DCM (20m) Frozen -80 °C

1 4 13/09/17 Water (250ml) CTD/bottles Amber glass bottle 1m Fixed w/Lugol’s

1 4 13/09/17 Water (250ml) CTD/bottles Amber glass bottle DCM (20m) Fixed w/Lugol’s

1 8 13/09/17 Plankton Multinet 20μm/ Phyto 4

Transparent flask - black cap 260-30 Fixed w/Lugol’s

1 8 13/09/17 Plankton Multinet 20μm/ Phyto 5 Plastic flask 30-0 Fixed w/Lugol’s

1 8 13/09/17 Plankton Multinet 20μm/ Phyto 4 Tube yellow cap 260-30 Frozen -80 °C

1 8 13/09/17 Plankton Multinet 20μm/ Phyto 5 Tube yellow cap 30-0 Frozen -80 °C

3 23 14/09/17 Water (10L) CTD/bottles Filter in cryotube bottom (350m) Frozen -80 °C

3 25 14/09/17 Water (10L) CTD/bottles Filter in cryotube 1m Frozen -80 °C

3 25 14/09/17 Water (10L) CTD/bottles Filter in cryotube DCM (20m) Frozen -80 °C

3 23 14/09/17 Water (250ml) CTD/bottles Amber glass bottle bottom Fixed w/Lugol’s

3 25 14/09/17 Water (250ml) CTD/bottles Amber glass bottle 1m Fixed w/Lugol’s

3 25 14/09/17 Water (250ml) CTD/bottles Amber glass bottle DCM (20m) Fixed w/Lugol’s

3 29 14/09/17 Plankton Multinet 20μm/ Phyto 4

Transparent flask - black cap 350-30 Fixed w/Lugol’s

3 29 14/09/17 Plankton Multinet 20μm/ Phyto 5

Transparent flask - black cap 30-0 Fixed w/Lugol’s

3 29 14/09/17 Plankton Multinet 20μm/ Phyto 4 Tube yellow cap 350-30 Frozen -80 °C

3 29 14/09/17 Plankton Multinet 20μm/ Phyto 5 Tube yellow cap 30-0 Frozen -80 °C

5 44 15/09/17 Water (10L) CTD/bottles Filter in cryotube bottom (135m) Frozen -80 °C

5 46 15/09/17 Water (10L) CTD/bottles Filter in cryotube 1m Frozen -80 °C

5 46 15/09/17 Water (10L) CTD/bottles Filter in cryotube DCM (27m) Frozen -80 °C

5 46 15/09/17 Water (250ml) CTD/bottles Amber glass bottle 1m Fixed w/Lugol’s

5 46 15/09/17 Water (250ml) CTD/bottles Amber glass bottle DCM (27m) Fixed w/Lugol’s

5 44 15/09/17 Water (250ml) CTD/bottles Amber glass bottle bottom (135m) Fixed w/Lugol’s

5b 56 15/09/17 Plankton Multinet 20μm/ Phyto 4

Transparent flask - black cap 200-30 Fixed w/Lugol’s

5b 56 15/09/17 Plankton Multinet 20μm/ Phyto 5 Plastic flask 30-0 Fixed w/Lugol’s

5b 56 15/09/17 Plankton Multinet 20μm/ Phyto 4 Tube yellow cap 200-30 Frozen -80 °C

5b 56 15/09/17 Plankton Multinet 20μm/ Phyto 5 Tube yellow cap 30-0 Frozen -80 °C

5b 54 15/09/17 Water (10L) CTD/bottles Filter in cryotube 210 Frozen -80 °C

38

5b 54 15/09/17 Water (10L) CTD/bottles Filter in cryotube 1m Frozen -80 °C

5b 54 15/09/17 Water (10L) CTD/bottles Filter in cryotube DCM (25m) Frozen -80 °C

5b 54 15/09/17 Water (250ml) CTD/bottles Amber glass bottle 1m Fixed w/Lugol’s

5b 54 15/09/17 Water (250ml) CTD/bottles Amber glass bottle DCM(25m) Fixed w/Lugol’s

5b 54 15/09/17 Water (250ml) CTD/bottles Amber glass bottle bottom (210m) Fixed w/Lugol’s

7 60 16/09/17 Water (10L) CTD/bottles Filter in cryotube bottom (360m) Frozen -80 °C

7 62 16/09/17 Water (10L) CTD/bottles Filter in cryotube 1m Frozen -80 °C

7 62 16/09/17 Water (10L) CTD/bottles Filter in cryotube DCM (20m) Frozen -80 °C

7 60 16/09/17 Water (250ml) CTD/bottles Amber glass bottle bottom Fixed w/Lugol’s

7 62 16/09/17 Water (250ml) CTD/bottles Amber glass bottle 1m Fixed w/Lugol’s

7 62 16/09/17 Water (250ml) CTD/bottles Amber glass bottle DCM (20m) Fixed w/Lugol’s

7 67 16/09/17 Plankton Multinet 20μm/ Phyto 4

Transparent flask - black cap 360-30 Fixed w/Lugol’s

7 67 16/09/17 Plankton Multinet 20μm/ Phyto 5

Transparent flask - black cap 30-0 Fixed w/Lugol’s

7 67 16/09/17 Plankton Multinet 20μm/ Phyto 4 Tube yellow cap 360-30 Frozen -80 °C

7 67 16/09/17 Plankton Multinet 20μm/ Phyto 5 Tube yellow cap 30-0 Frozen -80 °C

8 82 17/09/17 Water (10L) CTD/bottles Filter in cryotube bottom (570m) Frozen -80 °C

8 84 17/09/17 Water (10L) CTD/bottles Filter in cryotube 1m Frozen -80 °C

8 84 17/09/17 Water (10L) CTD/bottles Filter in cryotube DCM (35m) Frozen -80 °C

8 82 17/09/17 Water (250ml) CTD/bottles Amber glass bottle bottom (570m) Fixed w/Lugol’s

8 84 17/09/17 Water (250ml) CTD/bottles Amber glass bottle 1m Fixed w/Lugol’s

8 84 17/09/17 Water (250ml) CTD/bottles Amber glass bottle DCM (35m) Fixed w/Lugol’s

8 87 17/09/17 Plankton Multinet 20μm/ Phyto 4

Transparent flask - black cap 500-30 Fixed w/Lugol’s

8 87 17/09/17 Plankton Multinet 20μm/ Phyto 5

Transparent flask - black cap 30-0 Fixed w/Lugol’s

8 87 17/09/17 Plankton Multinet 20μm/ Phyto 4 Tube yellow cap 500-30 Frozen -80 °C

8 87 17/09/17 Plankton Multinet 20μm/ Phyto 5 Tube yellow cap 30-0 Frozen -80 °C

10 101 18/09/17 Water (10L) CTD/bottles Filter in cryotube bottom (485m) Frozen -80 °C

10 104 18/09/17 Water (10L) CTD/bottles Filter in cryotube 1m Frozen -80 °C

10 104 18/09/17 Water (10L) CTD/bottles Filter in cryotube DCM (20m) Frozen -80 °C

10 101 18/09/17 Water (250ml) CTD/bottles Amber glass bottle bottom (485m) Fixed w/Lugol’s

10 104 18/09/17 Water (250ml) CTD/bottles Amber glass bottle 1m Fixed w/Lugol’s

10 104 18/09/17 Water (250ml) CTD/bottles Amber glass bottle DCM (20m) Fixed w/Lugol’s

10 107 18/09/17 Plankton Multinet 20μm/ Phyto 4

Transparent flask - black cap 485-30 Fixed w/Lugol’s

10 107 18/09/17 Plankton Multinet 20μm/ Phyto 5

Transparent flask - black cap 30-0 Fixed w/Lugol’s

10 107 18/09/17 Plankton Multinet 20μm/ Phyto 4 Tube yellow cap 485-30 Frozen -80 °C

Station Activity Date Source Instrument Sample holder Water depth (m) Treatment

39

10 107 18/09/17 Plankton Multinet 20μm/ Phyto 5 Tube yellow cap 30-0 Frozen -80 °C

12 125 19/09/17 Water (10L) CTD/bottles Filter in cryotube bottom (485m) Frozen -80 °C

12 127 19/09/17 Water (10L) CTD/bottles Filter in cryotube 1m Frozen -80 °C

12 127 19/09/17 Water (10L) CTD/bottles Filter in cryotube DCM (30m) Frozen -80 °C

12 125 19/09/17 Water (250ml) CTD/bottles Amber glass bottle bottom (485m) Fixed w/Lugol’s

12 127 19/09/17 Water (250ml) CTD/bottles Amber glass bottle 1m Fixed w/Lugol’s

12 127 19/09/17 Water (250ml) CTD/bottles Amber glass bottle DCM (30m) Fixed w/Lugol’s

12 131 19/09/17 Plankton Multinet 20μm/ Phyto 4

Transparent flask - black cap 485-30 Fixed w/Lugol’s

12 131 19/09/17 Plankton Multinet 20μm/ Phyto 5

Transparent flask - black cap 30-0 Fixed w/Lugol’s

12 131 19/09/17 Plankton Multinet 20μm/ Phyto 4 Tube yellow cap 485-30 Frozen -80 °C

12 131 19/09/17 Plankton Multinet 20μm/ Phyto 5 Tube yellow cap 30-0 Frozen -80 °C

13 140 20/09/17 Water (10L) CTD/bottles Filter in cryotube bottom (380m) Frozen -80 °C

13 142 20/09/17 Water (10L) CTD/bottles Filter in cryotube 1m Frozen -80 °C

13 142 20/09/17 Water (10L) CTD/bottles Filter in cryotube DCM (23m) Frozen -80 °C

13 140 20/09/17 Water (250ml) CTD/bottles Amber glass bottle bottom (380m) Fixed w/Lugol’s

13 142 20/09/17 Water (250ml) CTD/bottles Amber glass bottle 1m Fixed w/Lugol’s

13 142 20/09/17 Water (250ml) CTD/bottles Amber glass bottle DCM (23m) Fixed w/Lugol’s

13 147 20/09/17 Plankton Multinet 20μm/ Phyto 4

Transparent flask - black cap 360-30 Fixed w/Lugol’s

13 147 20/09/17 Plankton Multinet 20μm/ Phyto 5

Transparent flask - black cap 30-0 Fixed w/Lugol’s

13 147 20/09/17 Plankton Multinet 20μm/ Phyto 4 Tube yellow cap 360-30 Frozen -80 °C

13 147 20/09/17 Plankton Multinet 20μm/ Phyto 5 Tube yellow cap 30-0 Frozen -80 °C

14 158 21/09/17 Water (10L) CTD/bottles Filter in cryotube bottom (330m) Frozen -80 °C

14 160 21/09/17 Water (10L) CTD/bottles Filter in cryotube 1m Frozen -80 °C

14 160 21/09/17 Water (10L) CTD/bottles Filter in cryotube DCM (50m) Frozen -80 °C

14 158 21/09/17 Water (250ml) CTD/bottles Amber glass bottle bottom (330m) Fixed w/Lugol’s

14 160 21/09/17 Water (250ml) CTD/bottles Amber glass bottle 1m Fixed w/Lugol’s

14 160 21/09/17 Water (250ml) CTD/bottles Amber glass bottle DCM (50m) Fixed w/Lugol’s

14 164 21/09/17 Plankton Multinet 20μm/ Phyto 4

Transparent flask - black cap 300-30 Fixed w/Lugol’s

14 164 21/09/17 Plankton Multinet 20μm/ Phyto 5

Transparent flask - black cap 30-0 Fixed w/Lugol’s

14 164 21/09/17 Plankton Multinet 20μm/ Phyto 4 Tube yellow cap 300-30 Frozen -80 °C

14 164 21/09/17 Plankton Multinet 20μm/ Phyto 5 Tube yellow cap 30-0 Frozen -80 °C

16 184 22/09/17 Water (10L) CTD/bottles Filter in cryotube bottom (155m) Frozen -80 °C

16 186 22/09/17 Water (10L) CTD/bottles Filter in cryotube 1m Frozen -80 °C

Station Activity Date Source Instrument Sample holder Water depth (m) Treatment

40

16 186 22/09/17 Water (10L) CTD/bottles Filter in cryotube DCM (15m) Frozen -80 °C

16 184 22/09/17 Water (250ml) CTD/bottles Amber glass bottle bottom (155m) Fixed w/Lugol’s

16 186 22/09/17 Water (250ml) CTD/bottles Amber glass bottle 1m Fixed w/Lugol’s

16 186 22/09/17 Water (250ml) CTD/bottles Amber glass bottle DCM (15m) Fixed w/Lugol’s

16 190 22/09/17 Plankton Multinet 20μm/ Phyto 4

Transparent flask - black cap 130-30 Fixed w/Lugol’s

16 190 22/09/17 Plankton Multinet 20μm/ Phyto 5

Transparent flask - black cap 30-0 Fixed w/Lugol’s

16 190 22/09/17 Plankton Multinet 20μm/ Phyto 4 Tube yellow cap 130-30 Frozen -80 °C

16 190 22/09/17 Plankton Multinet 20μm/ Phyto 5 Tube yellow cap 30-0 Frozen -80 °C

19 219 22/09/17 Water (10L) CTD/bottles Filter in cryotube bottom (326m) Frozen -80 °C

19 221 22/09/17 Water (10L) CTD/bottles Filter in cryotube 1m Frozen -80 °C

19 221 22/09/17 Water (10L) CTD/bottles Filter in cryotube DCM (20m) Frozen -80 °C

19 219 22/09/17 Water (250ml) CTD/bottles Amber glass bottle bottom (326m) Fixed w/Lugol’s

19 221 22/09/17 Water (250ml) CTD/bottles Amber glass bottle 1m Fixed w/Lugol’s

19 221 22/09/17 Water (250ml) CTD/bottles Amber glass bottle DCM (20m) Fixed w/Lugol’s

19 225 22/09/17 Plankton Multinet 20μm/ Phyto 4

Transparent flask - black cap 300-30 Fixed w/Lugol’s

19 225 22/09/17 Plankton Multinet 20μm/ Phyto 5

Transparent flask - black cap 30-0 Fixed w/Lugol’s

19 225 22/09/17 Plankton Multinet 20μm/ Phyto 4 Tube yellow cap 300-30 Frozen -80 °C

19 225 22/09/17 Plankton Multinet 20μm/ Phyto 5 Tube yellow cap 30-0 Frozen -80 °C

Station Activity Date Source Instrument Sample holder Water depth (m) Treatment

41

Appendix 2. Sediment cores – deployment and recovery Station Event Gear Latitude

(dec; North) Longitude (dec, West)

Water depth (m)

Date Time (UTC)

Success /Fail

Core name Recovery (cm)

1 10 Rumohr 79.62973333 -6.070416667 319.6 2017-09-13 14:45:07 S DA17-NG-ST1-10R

92.6

11 Rumohr 79.62903333 -6.075766667 321.5 2017-09-13 15:00:50 S DA17-NG-ST1-11R

69.5

12 Rumohr 79.62945 -6.049466667 325.3 2017-09-13 15:22:36 S DA17-NG-ST1-12R

84

13 Rumohr 79.63 -6.05815 325.2 2017-09-13 16:10:18 F FAIL -

14 Rumohr 79.62988333 -6.061616667 323.3 2017-09-13 16:24:57 S DA17-NG-ST1-14R

83.7

15 Rumohr 79.62961667 -6.062066667 322.5 2017-09-13 16:40:57 S DA17-NG-ST1-15R

59.7

16 Rumohr 79.63018333 -6.064733333 320.5 2017-09-13 16:55:55 F FAIL -

17 Rumohr 79.63121667 -6.063566667 324.5 2017-09-13 17:12:31 S DA17-NG-ST1-17R

85

18 Rumohr 79.63265 -6.061483333 324 2017-09-13 17:28:42 S DA17-NG-ST1-18R

82

19 Gravity 79.63378333 -6.051166667 322.5 2017-09-13 18:04:16 S DA17-NG-ST1-19G

150

3 30 Rumohr 80.03531667 -8.962466667 382.3 2017-09-14 16:07:02 S DA17-NG-ST3-30R

86.6

31 Rumohr 80.03905 -8.965783333 377.9 2017-09-14 16:29:52 S DA17-NG-ST3-31R

89.3

32 Rumohr 80.04263333 -8.9677 376.6 2017-09-14 16:47:47 S DA17-NG-ST3-32R

91.4

33 Rumohr 80.04115 -8.96885 377.5 2017-09-14 17:06:02 S DA17-NG-ST3-33R

90.3

34 Rumohr 80.04103333 -8.972783333 375.3 2017-09-14 17:22:24 S DA17-NG-ST3-34R

91

35 Rumohr 80.04086667 -8.97585 374.4 2017-09-14 17:38:49 S DA17-NG-ST3-35R

93

36 Rumohr 80.04075 -8.975233333 374.4 2017-09-14 17:55:28 S DA17-NG-ST3-36R

156.5

39 Gravity 80.03716667 -8.923183333 390.6 2017-09-14 20:58:05 S DA17-NG-ST3-39G

320

5 51 Gravity 79.82486667 -12.47615 220.4 2017-09-15 13:38:52 S DA17-NG-ST5-51G

30

52 Rumohr 79.82398333 -12.46863333 225.9 2017-09-15 14:06:26 S DA17-NG-ST5-52R

30.2

7 68 Rumohr 79.07068333 -11.90788333 383 2017-09-16 11:29:57 S DA17-NG-ST7-68R

97.5

69 Rumohr 79.07151667 -11.90021667 384.5 2017-09-16 11:47:08 S DA17-NG-ST7-69R

148

70 Rumohr 79.07171667 -11.89855 385.1 2017-09-16 12:07:04 S DA17-NG-ST7-70R

188

71 Rumohr 79.0718 -11.89268333 386 2017-09-16 12:23:47 S DA17-NG-ST7-71R

93

72 Rumohr 79.07215 -11.8881 384.6 2017-09-16 12:39:30 S DA17-NG-ST7-72R

88

73 Gravity 79.06833333 -11.90318333 385 2017-09-16 13:46:13 S DA17-NG-ST7-73G

410

79 Rumohr 79.06615 -11.93745 372.4 2017-09-16 15:35:37 S DA17-NG-ST7-79R

179

80 Gravity 79.10085 -12.16405 309.5 2017-09-16 16:48:36 S DA17-NG-ST7-80G

350

8 89 Rumohr 78.50088333 -17.29008333 587.4 2017-09-17 11:24:13 S DA17-NG-ST8-89R

94

90 Rumohr 78.50001667 -17.30718333 594.9 2017-09-17 11:48:52 S DA17-NG-ST8-90R

125

42

91 Rumohr 78.4999 -17.31943333 599.6 2017-09-17 12:13:21 S DA17-NG-ST8-91R

120

92 Gravity 78.5009 -17.27851667 582.9 2017-09-17 12:53:06 S DA17-NG-ST8-92G

585

96 Gravity 78.50011667 -17.35878333 602 2017-09-17 14:52:15 S DA17-NG-ST8-96G

530

97 Rumohr 78.49815 -17.3919 597.3 2017-09-17 15:30:54 S DA17-NG-ST8-97R

91

98 Rumohr 78.49625 -17.40426667 594.9 2017-09-17 15:56:17 S DA17-NG-ST8-98R

99

10 108 Rumohr 77.95045 -15.5064 504 2017-09-18 10:44:54 S DA17-NG-ST10-108R

92.5

109 Rumohr 77.94966667 -15.49391667 503.8 2017-09-18 11:08:33 S DA17-NG-ST10-109R

142

110 Gravity 77.95008333 -15.50853333 503.9 2017-09-18 11:52:30 S DA17-NG-ST10-110G

70

114 Rumohr 77.95096667 -15.51881667 503.2 2017-09-18 13:37:29 F FAIL -

115 Rumohr 77.95095 -15.51305 503 2017-09-18 13:56:47 F FAIL -

116 Rumohr 77.95146667 -15.50555 503.4 2017-09-18 14:16:02 S DA17-NG-ST10-116R

155

117 Gravity 77.95861667 -15.44943333 497.2 2017-09-18 14:56:49 S DA17-NG-ST10-117G

410

118 Rumohr 77.95861667 -15.42611667 493.6 2017-09-18 15:25:53 F FAIL -

119 Rumohr 77.95951667 -15.42198333 495.4 2017-09-18 15:37:50 F FAIL -

120 Rumohr 77.96095 -15.41756667 496.8 2017-09-18 15:49:59 S DA17-NG-ST10-120R

86

121 Rumohr 77.95753333 -15.45415 499.1 2017-09-18 16:21:07 S DA17-NG-ST10-121R

50

12 132 Rumohr 77.1271 -10.6802 501.1 2017-09-19 13:05:39 S DA17-NG-ST12-132R

88

133 Rumohr 77.12615 -10.67251667 500.9 2017-09-19 13:28:16 S DA17-NG-ST12-133R

107

134 Rumohr 77.12505 -10.6632 500.5 2017-09-19 13:51:28 S DA17-NG-ST12-134R

146

135 Gravity 77.12746667 -10.67565 500.9 2017-09-19 14:49:54 S DA17-NG-ST12-135G

270

13 148 Rumohr 75.84815 -12.5931 397.1 2017-09-20 11:45:05 S DA17-NG-ST13-148R

78

149 Rumohr 75.84826667 -12.594 398 2017-09-20 12:01:33 S DA17-NG-ST13-149R

80

150 Rumohr 75.84846667 -12.59526667 398.5 2017-09-20 12:18:32 S DA17-NG-ST13-150R

90

151 Rumohr 75.84851667 -12.5967 398.7 2017-09-20 12:35:08 S DA17-NG-ST13-151R

120

152 Gravity 75.84765 -12.59205 397.2 2017-09-20 13:10:16 S DA17-NG-ST13-152G

190

14 165 Rumohr 74.09138333 -19.42856667 340.1 2017-09-21 10:34:31 F FAIL -

166 Rumohr 74.09105 -19.43291667 342.4 2017-09-21 10:51:29 S DA17-NG-ST14-166R

85

167 Rumohr 74.09115 -19.43305 342.6 2017-09-21 11:06:55 S DA17-NG-ST14-167R

80

168 Rumohr 74.09088333 -19.43168333 341.6 2017-09-21 11:21:44 S DA17-NG-ST14-168R

89

169 Rumohr 74.09048333 -19.43295 341.5 2017-09-21 11:37:23 F FAIL -

170 Rumohr 74.09023333 -19.43225 341.3 2017-09-21 11:51:11 F FAIL -

171 Gravity 74.09021667 -19.43103333 341.2 2017-09-21 12:20:14 S DA17-NG-ST14-171G

420

172 Rumohr 74.0901 -19.43035 341.4 2017-09-21 12:42:51 S DA17-NG-ST14-172R

84

173 Rumohr 74.09066667 -19.43261667 341.8 2017-09-21 12:59:10 S DA17-NG-ST14-173R

140

Station Event Gear Latitude (dec; North)

Longitude (dec, West)

Water depth (m)

Date Time (UTC)

Success /Fail

Core name Recovery (cm)

43

15 180 Gravity 74.20775 -19.03245 143.8 2017-09-21 17:02:02 S DA17-NG-ST15-180G

350

181 Rumohr 74.20593333 -19.032 143.8 2017-09-21 17:20:34 S DA17-NG-ST15-181R

90

182 Rumohr 74.20403333 -19.03418333 149.4 2017-09-21 17:39:50 S DA17-NG-ST15-182R

72

15 261 Rumohr 74.21098333 -19.0168 146.8 2017-09-24 10:57:43 F FAIL -

16 191 Rumohr 74.30868333 -20.29331667 157.4 2017-09-22 10:24:11 S DA17-NG-ST16-191R

91

192 Rumohr 74.3084 -20.29453333 158.7 2017-09-22 10:32:10 S DA17-NG-ST16-192R

91

193 Rumohr 74.30915 -20.29303333 154.9 2017-09-22 10:40:07 S DA17-NG-ST16-193R

91

194 Rumohr 74.3086 -20.29506667 158.9 2017-09-22 10:49:26 F FAIL -

195 Rumohr 74.30888333 -20.29511667 158.8 2017-09-22 10:57:45 S DA17-NG-ST16-195R

185

196 Rumohr 74.30851667 -20.29663333 159 2017-09-22 11:07:44 F FAIL -

197 Rumohr 74.30886667 -20.29665 159.2 2017-09-22 11:17:18 F FAIL -

198 Rumohr 74.309 -20.29936667 159 2017-09-22 11:23:51 F FAIL -

199 Rumohr 74.30923333 -20.30006667 159.7 2017-09-22 12:03:48 F FAIL -

200 Rumohr 74.30906667 -20.30106667 159.2 2017-09-22 12:05:32 S DA17-NG-ST16-200R

90

201 Rumohr 74.30911667 -20.3022 158.9 2017-09-22 12:13:22 S DA17-NG-ST16-201R

190

202 Rumohr 74.3092 -20.29746667 159.4 2017-09-22 12:24:27 S DA17-NG-ST16-202R

146

203 Gravity 74.30846667 -20.2921 157.8 2017-09-22 12:54:27 S DA17-NG-ST16-203G

160

208 Rumohr 74.30866667 -20.29505 159.6 2017-09-22 14:23:53 F FAIL -

209 Rumohr 74.30798333 -20.30045 158.1 2017-09-22 14:32:23 F FAIL -

210 Gravity 74.30758333 -20.29603333 158.9 2017-09-22 15:30:26 S DA17-NG-ST16-210G

170

18 213 Gravity 74.34908333 -20.33831667 168.1 2017-09-22 17:23:14 S DA17-NG-ST18-213G

310

214 Rumohr 74.34928333 -20.34 167.5 2017-09-22 17:35:52 S DA17-NG-ST18-214R

90

215 Rumohr 74.3488 -20.33715 168.2 2017-09-22 17:55:55 S DA17-NG-ST18-215R

90

216 Rumohr 74.34918333 -20.33536667 168.3 2017-09-22 18:05:12 S DA17-NG-ST18-216R

88

19 226 Rumohr 74.46308333 -21.18826667 332.2 2017-09-23 10:20:53 S DA17-NG-ST19-226R

91

227 Rumohr 74.46291667 -21.1887 332.3 2017-09-23 10:31:51 S DA17-NG-ST19-227R

228 Rumohr 74.46356667 -21.19156667 332.4 2017-09-23 10:46:00 S DA17-NG-ST19-228R

92

229 Rumohr 74.46335 -21.19031667 332.5 2017-09-23 11:00:45 F FAIL

230 Rumohr 74.46303333 -21.19026667 332.6 2017-09-23 11:17:14 S DA17-NG-ST19-230R

231 Rumohr 74.4632 -21.18976667 332.7 2017-09-23 11:37:27 S DA17-NG-ST19-231R

232 Rumohr 74.46303333 -21.19125 332.8 2017-09-23 11:52:27 S DA17-NG-ST19-232R

159

233 Rumohr 74.46321667 -21.19551667 332.9 2017-09-23 12:07:11 F FAIL -

234 Rumohr 74.46295 -21.1951 333 2017-09-23 12:19:03 F FAIL -

235 Gravity 74.46313333 -21.19083333 333.1 2017-09-23 12:49:28 S DA17-NG-ST19-235G

370

21 243 Rumohr 74.42143333 -20.50561667 146.5 2017-09-23 18:40:17 S DA17-NG-ST21-243R

92

Station Event Gear Latitude (dec; North)

Longitude (dec, West)

Water depth (m)

Date Time (UTC)

Success /Fail

Core name Recovery (cm)

44

244 Rumohr 74.42213333 -20.50746667 150.2 2017-09-23 18:48:03 S DA17-NG-ST21-244R

245 Gravity 74.42346667 -20.51488333 156.5 2017-09-23 19:10:31 S DA17-NG-ST21-245G

360

22 252 Gravity 74.44291667 -18.71883333 147.1 2017-09-24 06:54:11 S DA17-NG-ST22-252G

230

253 Rumohr 74.44376667 -18.72195 146.8 2017-09-24 07:20:13 S DA17-NG-ST22-253R

71

254 Rumohr 74.442 -18.71453333 144.6 2017-09-24 07:37:47 F FAIL -

255 Rumohr 74.44583333 -18.72883333 145 2017-09-24 07:51:28 F FAIL -

256 Rumohr 74.44451667 -18.7224 146.2 2017-09-24 07:59:47 S DA17-NG-ST22-256R

97

Station Event Gear Latitude (dec; North)

Longitude (dec, West)

Water depth (m)

Date Time (UTC)

Success /Fail

Core name Recovery (cm)

45

Appendix 3. Surface sediment recovery Station Event Gear Latitude

(dec; North) Longitude (dec, West)

Water depth (m)

Date Time (UTC)

Success /Fail

Core name

1 9 Box corer

79.63112 -06.05978 324.6 2017-09-13 13:54:15 S DA17-NG-ST1-009BC

3 37 Haps 80.04538 -08.96988 377.3 2017-09-14 18:18:13 S DA17-NG-ST03-037HAPS

38 Haps 80.05100 -08.96907 367.7 2017-09-14 18:38:32 S DA17-NG-ST03-038HAPS

40 Haps 80.03832 -08.84595 346.1 2017-09-14 21:35:50 S DA17-NG-ST03-040HAPS

41 Haps 80.03832 -08.81522 307.9 2017-09-14 22:03:04 S DA17-NG-ST03-041HAPS

4 42 Dredge 79.97473 -10.52147 124.3 2017-09-15 03:18:58 S DA17-NG-ST04-042DRGE

5 48 Haps 79.82748 -12.50123 205.4 2017-09-15 12:48:09 S DA17-NG-ST05-048HAPS

49 Haps 79.82702 -12.49468 206.7 2017-09-15 13:00:07 S DA17-NG-ST05-049HAPS

50 Haps 79.82660 -12.48978 211.8 2017-09-15 13:11:19 S DA17-NG-ST05-045HAPS

7 74 Haps 79.06965 -11.90626 384.6 2017-09-16 14:12:15 S DA17-NG-ST7-074HAPS

75 Haps 79.07008 -11.90750 382.9 2017-09-16 14:28:28 S DA17-NG-ST7-075HAPS

76 Haps 79.06932 -11.91028 384.4 2017-09-16 14:44:1 S DA17-NG-ST7-076HAPS

77 Haps 79.06910 -11.91590 382.2 2017-09-16 15:00:03 S DA17-NG-ST7-077HAPS

78 Haps 79.06875 -11.92265 377.3 2017-09-16 15:16:24 S DA17-NG-ST7-078HAPS

81 Dredge 79.04735 -11.95310 344.6 2017-09-16 17:56:12 S DA17-NG-ST07-081DRGE

8 93 Haps 78.49935 -17.29195 589.8 2017-09-17 13:26:08 S DA17-NG-ST08-093HAPS

94 Haps 78.49987 -17.30272 593.8 2017-09-17 13:48:58 S DA17-NG-ST08-094HAPS

95 Haps 78.50242 -17.31390 593.8 2017-09-17 14:12:00 S DA17-NG-ST08-095HAPS

10 111 Haps 77.95088 -15.50773 504 2017-09-18 12:24:34 S DA17-NG-ST10-111HAPS

112 Haps 77.95065 -15.50752 504 2017-09-18 12:45:27 S DA17-NG-ST10-112HAPS

113 Haps 77.95150 -15.49898 504.5 2017-09-18 13:06:14 S DA17-NG-ST10-113HAPS

11 122 Dredge 77.88683 -13.6282 349.2 2017-09-18 20:51:49 F DA17-NG-ST11-122DRGE

12 136 Haps 77.12798 -10.67650 500.6 2017-09-19 14:53:44 S DA17-NG-ST12-136HAPS

137 Haps 77.12810 -10.67268 498.7 2017-09-19 15:13:32 S DA17-NG-ST12-137HAPS

138 Haps 77.12797 -10.66585 500.4 2017-09-19 15:33:25 S DA17-NG-ST12-138HAPS

139 Haps 77.12777 -10.66072 500.7 2017-09-19 15:52:52 S DA17-NG-ST12-139HAPS

13 153 Haps 75.84782 -12.59382 397.5 2017-09-20 13:28:58 S DA17-NG-ST13-153HAPS

154 Haps 75.84705 -12.59233 397.6 2017-09-20 13:44:59 S DA17-NG-ST13-154HAPS

155 Haps 75.84753 -12.58878 396.2 2017-09-20 14:01:12 S DA17-NG-ST13-155HAPS

14 174 Haps 74.09867 -19.43258 342 2017-09-21 13:15:54 S DA17-NG-ST14-174HAPS

46

175 Haps 74.09105 -19.43088 341.6 2017-09-21 13:39:45 S DA17-NG-ST14-175HAPS

176 Haps 74.09088 -19.42832 340.5 2017-09-21 13:54:34 S DA17-NG-ST14-176HAPS

177 Haps 74.08993 -19.43000 340.8 2017-09-21 14:08:55 S DA17-NG-ST14-177HAPS

16 204 Haps 74.30905 -20.29192 156.7 2017-09-22 13:38:29 S DA17-NG-ST14-204HAPS

205 Haps 74.30862 -20.29037 154.8 2017-09-22 13:46:36 S DA17-NG-ST14-205HAPS

206 Haps 74.30778 -20.29087 157.2 2017-09-22 13:55:49 S DA17-NG-ST14-206HAPS

207 Haps 74.30757 -20.29562 159 2017-09-22 14:04:47 S DA17-NG-ST14-207HAPS

246 Haps 74.31047 -20.29928 158.8 2017-09-23 20:15:29 S DA17-NG-ST16-246HAPS

17 211 VanVeen Grab

74.30768 -20.25600 38.5 2017-09-22 16:20:35 S DA17-NG-ST17-211VV

212 VanVeen Grab

74.30683 -20.26085 46.5 2017-09-22 16:33:11 S DA17-NG-ST17-212VV

19 236 Haps 74.46387 -21.19098 333 2017-09-23 13:28:20 S DA17-NG-ST19-236HAPS

237 Haps 74.46407 -21.19455 333.1 2017-09-23 13:48:22 S DA17-NG-ST19-237HAPS

238 Haps 74.46395 -21.33356 333.1 2017-09-23 14:02:10 S DA17-NG-ST19-238HAPS

239 Haps 74.46415 -21.20368 333.2 2017-09-23 14:15:25 S DA17-NG-ST19-239HAPS

240 Haps 74.46482 -21.20643 333 2017-09-23 14:29:02 S DA17-NG-ST19-240HAPS

22 257 Haps 74.44443 -18.72207 147.1 2017-09-24 08:13:53 S DA17-NG-ST22-257HAPS

258 Haps 74.44438 -18.72567 146.8 2017-09-24 08:21:55 S DA17-NG-ST22-258HAPS

259 Haps 74.44365 -18.72722 144.6 2017-09-24 08:31:41 S DA17-NG-ST22-259HAPS

Station Event Gear Latitude Longitude Water Date Time Success Core name

47

Appendix 4. Detailed lists of all casts deployed during the NorthGreen2017 Expedition

page 48-53

Dep

loym

ent 

no.

Statiopn

 no.

Nam

eInstrumen

tStatus

Time Start d

eploym

ent 

(UTC

)Latitud

e Start

Long

itude

 Start

Water dep

th 

Start

timeS

top (UTC

)Latitud

e Stop

Long

itude

 Stop

Water dep

th 

Stop

Wind Sp

eed

1Station 01

DA17

‐NG‐ST0

1‐00

1CTD

SEA (CTD

)Su

ccess

2017

‐09‐13

T08:14

:01

79.37.23

6 N

006.03

.535

 W32

0.9

2017

‐09‐13

T08:59

:14

79.37.01

1 N

006.02

.853

 W32

2.8

7.08

2Station 01

DA17

‐NG‐ST0

1‐00

2TURB

Turbulen

ce  

Success

2017

‐09‐13

T09:11

:23

79.36.94

4 N

006.03

.370

 W31

9.9

2017

‐09‐13

T09:17

:20

79.36.96

4 N

006.03

.240

 W32

0.9

6.48

3Station 01

DA17

‐NG‐ST0

1‐00

3MN

MULTI N

etSu

ccess

2017

‐09‐13

T09:43

:22

79.36.72

4 N

006.03

.100

 W32

3.2

2017

‐09‐13

T10:07

:17

79.36.54

8 N

006.03

.656

 W31

9.6

5.8

4Station 01

DA17

‐NG‐ST0

1‐00

4CTD

SEA (CTD

)Su

ccess

2017

‐09‐13

T10:22

:24

79.36.44

9 N

006.04

.209

 W31

5.3

2017

‐09‐13

T10:33

:25

79.36.32

2 N

006.03

.836

 W31

75.53

5Station 01

DA17

‐NG‐ST0

1‐00

5MN

MULTI N

etFail

2017

‐09‐13

T10:49

:35

79.36.10

7 N

006.03

.231

 W31

6.4

2017

‐09‐13

T11:01

:05

79.35.96

1 N

006.03

.276

 W32

5.2

5.54

6Station 01

DA17

‐NG‐ST0

1‐00

6MN

MULTI N

etSu

ccess

2017

‐09‐13

T11:40

:39

79.35.62

8 N

006.01

.252

 W32

420

17‐09‐13

T11:59

:20

79.35.43

9 N

006.01

.171

 W32

2.3

6.1

7Station 01

DA17

‐NG‐ST0

1‐00

7WP3

WP3

  Net

Success

2017

‐09‐13

T12:13

:16

79.35.23

6 N

006.02

.236

 W32

2.4

2017

‐09‐13

T12:27

:36

79.35.05

7 N

006.02

.165

 W31

8.7

6.5

8Station 01

DA17

‐NG‐ST0

1‐00

8MN 

MULTI N

et 20m

ySu

ccess

2017

‐09‐13

T12:40

:14

79.34.89

5 N

006.02

.666

 W31

1.9

2017

‐09‐13

T12:56

:43

79.34.73

9 N

006.02

.705

 W32

0.6

5.97

9Station 01

DA17

‐NG‐ST0

1‐00

9BC

BOX  corer 

Success

2017

‐09‐13

T13:54

:15

79.37.86

7 N

006.03

.587

 W32

4.6

2017

‐09‐13

T14:08

:31

79.37.78

8 N

006.03

.558

 W32

56.75

10Station 01

DA17

‐NG‐ST0

1‐01

0RRu

moh

r lot 

Success

2017

‐09‐13

T14:45

:07

79.37.78

4 N

006.04

.225

 W31

9.6

2017

‐09‐13

T14:54

:29

79.37.76

0 N

006.04

.386

 W31

9.4

5.78

11Station 01

DA17

‐NG‐ST0

1‐01

1RRu

moh

r lot 

Success

2017

‐09‐13

T15:00

:50

79.37.74

2 N

006.04

.546

 W32

1.5

2017

‐09‐13

T15:11

:30

79.37.74

6 N

006.04

.849

 W32

05.07

12Station 01

DA17

‐NG‐ST0

1‐01

2RRu

moh

r lot 

Success

2017

‐09‐13

T15:22

:36

79.37.76

7 N

006.02

.968

 W32

5.3

2017

‐09‐13

T15:32

:55

79.37.72

4 N

006.03

.174

 W32

54.57

13Station 01

DA17

‐NG‐ST0

1‐01

3RRu

moh

r lot 

Fail

2017

‐09‐13

T16:10

:18

79.37.80

0 N

006.03

.489

 W32

5.2

2017

‐09‐13

T16:21

:14

79.37.79

5 N

006.03

.585

 W32

4.4

4.77

14Station 01

DA17

‐NG‐ST0

1‐01

4RRu

moh

r lot 

Success

2017

‐09‐13

T16:24

:57

79.37.79

3 N

006.03

.697

 W32

3.3

2017

‐09‐13

T16:35

:14

79.37.78

1 N

006.03

.770

 W32

2.6

4.21

15Station 01

DA17

‐NG‐ST0

1‐01

5RRu

moh

r lot 

Success

2017

‐09‐13

T16:40

:57

79.37.77

7 N

006.03

.724

 W32

2.5

2017

‐09‐13

T16:51

:12

79.37.79

0 N

006.03

.740

 W32

3.3

5.24

16Station 01

DA17

‐NG‐ST0

1‐01

6RRu

moh

r lot 

Fail

2017

‐09‐13

T16:55

:55

79.37.81

1 N

006.03

.884

 W32

0.5

2017

‐09‐13

T17:06

:18

79.37.84

7 N

006.03

.855

 W32

4.3

5.2

17Station 01

DA17

‐NG‐ST0

1‐01

7RRu

moh

r lot 

Success

2017

‐09‐13

T17:12

:31

79.37.87

3 N

006.03

.814

 W32

4.5

2017

‐09‐13

T17:23

:07

79.37.93

0 N

006.03

.757

 W32

5.4

4.65

18Station 01

DA17

‐NG‐ST0

1‐01

8RRu

moh

r lot 

Success

2017

‐09‐13

T17:28

:42

79.37.95

9 N

006.03

.689

 W32

420

17‐09‐13

T17:38

:59

79.38.01

5 N

006.03

.586

 W32

2.8

4.66

19Station 01

DA17

‐NG‐ST0

1‐01

6GGravity corer

Success

2017

‐09‐13

T18:04

:16

79.38.02

7 N

006.03

.070

 W32

2.5

2017

‐09‐13

T18:25

:18

79.38.08

5 N

006.02

.418

 W32

0.8

3.27

20Station 02

DA17

‐NG‐ST0

2‐02

0CTD

SEA (CTD

)Su

ccess

2017

‐09‐13

T22:24

:00

79.30.90

9 N

008.10

.446

 W21

1.7

2017

‐09‐13

T23:00

:10

79.30.46

6 N

008.10

.662

 W20

9.7

4.47

21Station 02

DA17

‐NG‐ST0

2‐02

1TURB

Turbulen

ce  

Success

2017

‐09‐13

T23:10

:01

79.30.36

9 N

008.11

.232

 W21

2.2

2017

‐09‐13

T23:17

:13

79.30.32

5 N

008.11

.544

 W21

2.2

3.46

22Station 02

DA17

‐NG‐ST0

2‐02

2MIK

MIK Net

Success

2017

‐09‐13

T23:38

:34

79.30.68

1 N

008.16

.019

 W21

3.9

2017

‐09‐14

T00:27

:16

79.31.82

3 N

008.27

.265

 W22

8.3

3.46

23Station 03

DA17

‐NG‐ST0

3‐02

3CTD

SEA (CTD

)Su

ccess

2017

‐09‐14

T10:25

:27

80.02.65

1 N

008.57

.293

 W37

6.1

2017

‐09‐14

T11:11

:37

80.02.25

8 N

008.54

.558

 W38

9.5

5.77

24Station 03

DA17

‐NG‐ST0

3‐02

4TURB

Turbulen

ce  

Success

2017

‐09‐14

T11:30

:10

80.02.06

4 N

008.53

.579

 W38

0.2

2017

‐09‐14

T11:37

:46

80.01.92

6 N

008.53

.365

 W37

3.5

4.18

25Station 03

DA17

‐NG‐ST0

3‐02

5CTD

SEA (CTD

)Su

ccess

2017

‐09‐14

T12:00

:44

80.02.73

4 N

008.52

.578

 W38

1.3

2017

‐09‐14

T12:10

:02

80.02.58

4 N

008.52

.448

 W37

9.6

4.79

26Station 03

DA17

‐NG‐ST0

3‐02

6MN

MULTI N

etSu

ccess

2017

‐09‐14

T12:22

:29

80.02.40

7 N

008.52

.341

 W37

9.6

2017

‐09‐14

T12:41

:41

80.02.29

4 N

008.52

.966

 W37

6.8

4.54

27Station 03

DA17

‐NG‐ST0

3‐02

7MN

MULTI N

etSu

ccess

2017

‐09‐14

T13:10

:15

80.02.38

3 N

008.52

.999

 W38

3.9

2017

‐09‐14

T13:31

:43

80.02.11

5 N

008.53

.816

 W38

1.8

4.87

28Station 03

DA17

‐NG‐ST0

3‐02

8WP3

WP3

 Net  

Success

2017

‐09‐14

T14:03

:52

80.01.92

2 N

008.53

.659

 W37

5.4

2017

‐09‐14

T14:31

:12

80.01.75

0 N

008.54

.031

 W37

6.5

6.17

29Station 03

DA17

‐NG‐ST0

3‐02

9MN

MULTI N

et 20m

ySu

ccess

2017

‐09‐14

T14:44

:24

80.01.72

6 N

008.54

.813

 W38

5.9

2017

‐09‐14

T15:08

:33

80.01.73

9 N

008.55

.536

 W38

4.9

6.73

30Station 03

DA17

‐NG‐ST0

3‐03

0RRu

moh

r lot 

Success

2017

‐09‐14

T16:07

:02

80.02.11

9 N

008.57

.748

 W38

2.3

2017

‐09‐14

T16:25

:03

80.02.29

1 N

008.57

.910

 W37

7.5

6.11

31Station 03

DA17

‐NG‐ST0

3‐03

1RRu

moh

r lot 

Success

2017

‐09‐14

T16:29

:52

80.02.34

3 N

008.57

.947

 W37

7.9

2017

‐09‐14

T16:44

:29

80.02.51

1 N

008.57

.972

 W37

6.3

7.04

32Station 03

DA17

‐NG‐ST0

3‐03

2RRu

moh

r lot 

Success

2017

‐09‐14

T16:47

:47

80.02.55

8 N

008.58

.062

 W37

6.6

2017

‐09‐14

T17:00

:26

80.02.56

7 N

008.58

.249

 W37

6.4

7.11

33Station 03

DA17

‐NG‐ST0

3‐03

3RRu

moh

r lot 

Success

2017

‐09‐14

T17:06

:02

80.02.46

9 N

008.58

.131

 W37

7.5

2017

‐09‐14

T17:18

:18

80.02.45

4 N

008.58

.285

 W37

5.5

6.73

34Station 03

DA17

‐NG‐ST0

3‐03

4RRu

moh

r lot 

Success

2017

‐09‐14

T17:22

:24

80.02.46

2 N

008.58

.367

 W37

5.3

2017

‐09‐14

T17:34

:56

80.02.45

7 N

008.58

.552

 W37

4.3

6.8

35Station 03

DA17

‐NG‐ST0

3‐03

5RRu

moh

r lot 

Success

2017

‐09‐14

T17:38

:49

80.02.45

2 N

008.58

.551

 W37

4.4

2017

‐09‐14

T17:51

:04

80.02.45

8 N

008.58

.575

 W37

4.1

6.96

36Station 03

DA17

‐NG‐ST0

3‐03

6RRu

moh

r lot 

Success

2017

‐09‐14

T17:55

:28

80.02.44

5 N

008.58

.514

 W37

4.4

2017

‐09‐14

T18:07

:43

80.02.50

0 N

008.58

.328

 W37

4.7

6.9

37Station 03

DA17

‐NG‐ST0

3‐03

7HAP

SHA

PS corer

Success

2017

‐09‐14

T18:18

:13

80.02.72

3 N

008.58

.193

 W37

7.3

2017

‐09‐14

T18:30

:44

80.02.86

8 N

008.57

.990

 W37

66.38

38Station 03

DA17

‐NG‐ST0

3‐03

8HAP

SHA

PS corer

Success

2017

‐09‐14

T18:38

:32

80.03.06

0 N

008.58

.144

 W36

7.7

2017

‐09‐14

T18:50

:45

80.03.17

6 N

008.57

.755

 W36

5.6

7.09

39Station 03

DA17

‐NG‐ST0

3‐03

9GGravity corer

Success

2017

‐09‐14

T20:58

:05

80.02.23

0 N

008.55

.391

 W39

0.6

2017

‐09‐14

T21:16

:09

80.02.30

9 N

008.53

.140

 W38

5.1

9.62

40Station 03

DA17

‐NG‐ST0

3‐04

0HAP

SHA

PS corer

Success

2017

‐09‐14

T21:35

:50

80.02.29

9 N

008.50

.757

 W34

6.1

2017

‐09‐14

T21:47

:25

80.02.32

2 N

008.49

.903

 W33

4.2

7.85

41Station 03

DA17

‐NG‐ST0

3‐04

1HAP

SHA

PS corer

Success

2017

‐09‐14

T22:03

:04

80.02.29

5 N

008.48

.913

 W30

7.9

2017

‐09‐14

T22:13

:50

80.02.25

7 N

008.48

.173

 W28

5.8

8.92

42Station 04

DA17

‐NG‐ST0

4‐04

2DRG

EDred

geSu

ccess

2017

‐09‐15

T03:18

:58

79.58.48

4 N

010.31

.288

 W12

4.3

2017

‐09‐15

T03:19

:05

79.58.48

7 N

010.31

.295

 W12

3.8

5.11

43Station 04

DA17

‐NG‐ST0

4‐04

3CTD

SEA (CTD

)Su

ccess

2017

‐09‐15

T03:42

:40

79.58.48

7 N

010.32

.324

 W12

5.9

2017

‐09‐15

T04:17

:28

79.58.65

0 N

010.34

.858

 W12

6.9

8.1

44Station 05

DA17

‐NG‐ST0

5‐04

4CTD

SEA (CTD

)Su

ccess

2017

‐09‐15

T07:52

:31

79.50.66

0 N

012.20

.310

 W15

6.2

2017

‐09‐15

T08:26

:53

79.50.97

9 N

012.20

.822

 W15

8.5

6.03

45Station 05

DA17

‐NG‐ST0

5‐04

5TURB

Turbulen

ce  

Success

2017

‐09‐15

T08:37

:11

79.51.20

5 N

012.20

.768

 W16

4.4

2017

‐09‐15

T08:44

:22

79.51.35

7 N

012.20

.486

 W16

2.1

5.44

46Station 05

DA17

‐NG‐ST0

5‐46

CTD

SEA (CTD

)Su

ccess

2017

‐09‐15

T09:07

:10

79.51.20

1 N

012.18

.325

 W17

3.2

2017

‐09‐15

T09:18

:53

79.51.31

1 N

012.18

.045

 W17

5.5

5.49

47Station 05

DA17

‐NG‐ST0

5‐47

MN

MULTI N

etSu

ccess

2017

‐09‐15

T09:32

:01

79.51.43

9 N

012.17

.751

 W17

3.4

2017

‐09‐15

T09:41

:55

79.51.49

3 N

012.17

.540

 W17

1.7

6.19

48Station 05

DA17

‐NG‐ST0

5‐04

8HAP

SHA

PS corer

Success

2017

‐09‐15

T12:41

:27

79.49.64

9 N

012.30

.074

 W20

5.4

2017

‐09‐15

T12:48

:09

79.49.62

6 N

012.29

.842

 W20

7.2

1.66

49Station 05

DA17

‐NG‐ST0

5‐04

9HAP

SHA

PS corer

Success

2017

‐09‐15

T12:53

:20

79.49.62

1 N

012.29

.681

 W20

6.7

2017

‐09‐15

T13:00

:07

79.49.59

3 N

012.29

.478

 W20

9.3

1.16

48

50Station 05

DA17

‐NG‐ST0

5‐05

0HAP

SHA

PS corer

Success

2017

‐09‐15

T13:04

:17

79.49.59

6 N

012.29

.351

 W21

1.8

2017

‐09‐15

T13:11

:19

79.49.58

3 N

012.29

.175

 W21

4.5

0.7

51Station 05

DA17

‐NG‐ST0

5‐05

1GGravity corer

Success

2017

‐09‐15

T13:38

:52

79.49.49

2 N

012.28

.569

 W22

0.4

2017

‐09‐15

T13:44

:12

79.49.47

1 N

012.28

.523

 W22

2.9

1.31

52Station 05

DA17

‐NG‐ST0

5‐05

2RRu

moh

r lot 

Success

2017

‐09‐15

T14:06

:26

79.49.43

9 N

012.28

.118

 W22

5.9

2017

‐09‐15

T14:23

:03

79.49.38

6 N

012.27

.872

 W23

2.6

4.74

53Station 05

DA17

‐NG‐ST0

5‐05

3TURB

Turbulen

ce  

Success

2017

‐09‐15

T14:26

:20

79.49.39

2 N

012.27

.767

 W23

3.4

2017

‐09‐15

T14:29

:26

79.49.41

0 N

012.27

.732

 W23

0.8

4.61

54Station 05

DA17

‐NG‐ST0

5‐05

3CTD

SEA (CTD

)Su

ccess

2017

‐09‐15

T14:35

:55

79.49.38

3 N

012.27

.756

 W23

3.8

2017

‐09‐15

T15:10

:07

79.49.32

0 N

012.27

.241

 W23

4.4

6.63

55Station 05

DA17

‐NG‐ST0

5‐05

5MN

MULTI N

etSu

ccess

2017

‐09‐15

T15:19

:50

79.49.27

0 N

012.26

.895

 W23

6.1

2017

‐09‐15

T15:30

:44

79.49.25

6 N

012.26

.964

 W23

6.7

7.23

56Station 05

DA17

‐NG‐ST0

5‐05

6MN

MULTI N

et 20m

ySu

ccess

2017

‐09‐15

T15:46

:49

79.49.15

8 N

012.26

.678

 W23

8.4

2017

‐09‐15

T15:57

:20

79.49.14

9 N

012.26

.627

 W23

6.3

0.12

57Station 05

DA17

‐NG‐ST0

5‐05

7CTD

SEA (CTD

)Su

ccess

2017

‐09‐15

T21:16

:31

79.22.54

5 N

012.07

.538

 W12

8.1

2017

‐09‐15

T21:37

:13

79.22.61

7 N

012.07

.301

 W12

90.09

58Station 06

DA17

‐NG‐ST0

6‐05

8TURB

Turbulen

ce  

Success

2017

‐09‐15

T21:44

:33

79.22.60

3 N

012.07

.061

 W13

6.8

2017

‐09‐15

T21:52

:49

79.22.62

5 N

012.06

.655

 W13

20.14

59Station 06

DA17

‐NG‐ST0

6‐05

9MIK

MIK Net

Success

2017

‐09‐15

T22:04

:59

79.22.28

7 N

012.06

.594

 W14

0.8

2017

‐09‐15

T22:46

:23

79.20.15

8 N

012.03

.632

 W17

9.9

1.81

60Station 07

DA17

‐NG‐ST0

7‐06

0CTD

SEA (CTD

)Su

ccess

2017

‐09‐16

T06:17

:57

79.04.36

1 N

011.55

.196

 W38

0.5

2017

‐09‐16

T07:15

:18

79.04.61

7 N

011.53

.220

 W37

4.6

5.92

61Station 07

DA17

‐NG‐ST0

7‐06

1TURB

Turbulen

ce  

Success

2017

‐09‐16

T07:23

:30

79.04.75

8 N

011.52

.516

 W36

8.1

2017

‐09‐16

T07:31

:21

79.04.85

9 N

011.51

.760

 W35

8.6

5.01

62Station 07

DA17

‐NG‐ST0

7‐06

2CTD

SEA (CTD

)Su

ccess

2017

‐09‐16

T07:53

:13

79.05.34

7 N

011.49

.431

 W33

2.8

2017

‐09‐16

T08:02

:47

79.05.41

7 N

011.48

.766

 W32

2.9

4.39

63Station 07

DA17

‐NG‐ST0

7‐06

3MN

MULTI N

etFail

2017

‐09‐16

T08:14

:55

79.05.54

2 N

011.47

.792

 W30

6.5

2017

‐09‐16

T08:21

:06

79.05.58

3 N

011.47

.385

 W30

3.1

4.21

64Station 07

DA17

‐NG‐ST0

7‐06

4MN

MULTI N

etSu

ccess

2017

‐09‐16

T09:04

:58

79.05.67

5 N

011.45

.477

 W29

8.3

2017

‐09‐16

T09:20

:50

79.05.67

2 N

011.44

.855

 W29

5.6

5.04

65Station 07

DA17

‐NG‐ST0

7‐06

5MN

MULTI N

etSu

ccess

2017

‐09‐16

T09:43

:46

79.04.78

0 N

011.50

.365

 W35

5.8

2017

‐09‐16

T10:05

:49

79.04.70

6 N

011.49

.001

 W35

6.7

0.48

66Station 07

DA17

‐NG‐ST0

7‐06

6WP3

WP3

 Net  

Success

2017

‐09‐16

T10:14

:07

79.04.57

2 N

011.48

.399

 W35

6.9

2017

‐09‐16

T10:34

:35

79.04.50

1 N

011.47

.200

 W34

9.3

0.29

67Station 07

DA17

‐NG‐ST0

7‐06

7MN

MULTI N

et 20m

ySu

ccess

2017

‐09‐16

T10:52

:07

79.04.10

3 N

011.53

.583

 W38

7.4

2017

‐09‐16

T11:12

:34

79.04.10

7 N

011.52

.369

 W38

8.6

0.25

68Station 07

DA17

‐NG‐ST0

7‐06

8RRu

moh

r lot 

Success

2017

‐09‐16

T11:29

:57

79.04.24

1 N

011.54

.473

 W38

320

17‐09‐16

T11:42

:20

79.04.29

3 N

011.54

.138

 W38

4.4

0.19

69Station 07

DA17

‐NG‐ST0

7‐06

9RRu

moh

r lot 

Success

2017

‐09‐16

T11:47

:08

79.04.29

1 N

011.54

.013

 W38

4.5

2017

‐09‐16

T11:59

:40

79.04.31

5 N

011.53

.955

 W38

4.6

0.06

70Station 07

DA17

‐NG‐ST0

7‐07

0RRu

moh

r lot 

Success

2017

‐09‐16

T12:07

:04

79.04.30

3 N

011.53

.913

 W38

5.1

2017

‐09‐16

T12:17

:49

79.04.32

6 N

011.53

.728

 W38

60.11

71Station 07

DA17

‐NG‐ST0

7‐07

1RRu

moh

r lot 

Success

2017

‐09‐16

T12:23

:47

79.04.30

8 N

011.53

.561

 W38

620

17‐09‐16

T12:36

:08

79.04.33

5 N

011.53

.322

 W38

60.14

72Station 07

DA17

‐NG‐ST0

7‐07

2RRu

moh

r lot 

Success

2017

‐09‐16

T12:39

:30

79.04.32

9 N

011.53

.286

 W38

4.6

2017

‐09‐16

T12:52

:30

79.04.35

1 N

011.52

.992

 W38

3.6

0.28

73Station 07

DA17

‐NG‐ST0

7‐07

3GGravity corer

Success

2017

‐09‐16

T13:46

:13

79.04.10

0 N

011.54

.191

 W38

520

17‐09‐16

T13:58

:06

79.04.17

4 N

011.54

.252

 W38

5.5

0.39

74Station 07

DA17

‐NG‐ST0

7‐07

4HAP

SHA

PS  corer

Success

2017

‐09‐16

T14:12

:15

79.04.17

9 N

011.54

.376

 W38

4.6

2017

‐09‐16

T14:25

:13

79.04.20

9 N

011.54

.436

 W38

2.8

0.11

75Station 07

DA17

‐NG‐ST0

7‐07

5HAP

SHA

PS  corer

Success

2017

‐09‐16

T14:28

:28

79.04.20

5 N

011.54

.450

 W38

2.9

2017

‐09‐16

T14:41

:06

79.04.17

1 N

011.54

.564

 W38

4.6

0.15

76Station 07

DA17

‐NG‐ST0

7‐07

6HAP

SHA

PS  corer

Success

2017

‐09‐16

T14:44

:13

79.04.15

9 N

011.54

.617

 W38

4.4

2017

‐09‐16

T14:57

:10

79.04.12

7 N

011.54

.927

 W38

2.1

0.34

77Station 07

DA17

‐NG‐ST0

7‐07

7HAP

SHA

PS  corer

Success

2017

‐09‐16

T15:00

:03

79.04.14

6 N

011.54

.954

 W38

2.2

2017

‐09‐16

T15:12

:40

79.04.13

9 N

011.55

.212

 W37

8.9

0.31

78Station 07

DA17

‐NG‐ST0

7‐07

8HAP

SHA

PS  corer

Success

2017

‐09‐16

T15:16

:24

79.04.12

5 N

011.55

.359

 W37

7.3

2017

‐09‐16

T15:28

:58

79.04.03

9 N

011.55

.896

 W37

3.5

0.42

79Station 07

DA17

‐NG‐ST0

7‐07

9RRu

moh

r lot 

Success

2017

‐09‐16

T15:35

:37

79.03.96

9 N

011.56

.247

 W37

2.4

2017

‐09‐16

T15:48

:03

79.03.94

8 N

011.56

.451

 W37

1.4

0.08

80Station 07

DA17

‐NG‐ST0

7‐08

0GGravity corer

Success

2017

‐09‐16

T16:48

:36

79.06.05

1 N

012.09

.843

 W30

9.5

2017

‐09‐16

T16:57

:51

79.05.96

0 N

012.10

.095

 W30

60.52

81Station 07

DA17

‐NG‐ST0

7‐08

1DRG

EDred

geSu

ccess

2017

‐09‐16

T17:56

:12

79.02.84

1 N

011.57

.186

 W34

4.6

2017

‐09‐16

T18:23

:27

79.02.63

2 N

011.57

.699

 W31

80.17

82Station 07

DA17

‐NG‐ST0

7‐08

2CTD

SEA (CTD

)Su

ccess

2017

‐09‐17

T06:11

:04

78.29.97

3 N

017.17

.851

 W59

2.7

2017

‐09‐17

T07:18

:00

78.29.68

1 N

017.20

.428

 W59

8.4

0.37

83Station 08

DA17

‐NG‐ST0

8‐08

3TURB

Turbulen

ce  

Success

2017

‐09‐17

T07:24

:31

78.29.64

5 N

017.20

.686

 W59

9.3

2017

‐09‐17

T07:33

:04

78.29.66

2 N

017.21

.010

 W59

8.7

0.12

84Station 08

DA17

‐NG‐ST0

8‐08

4CTD

SEA (CTD

)Su

ccess

2017

‐09‐17

T07:45

:50

78.29.61

6 N

017.21

.609

 W59

5.1

2017

‐09‐17

T07:58

:02

78.29.52

9 N

017.22

.203

 W59

7.2

0.46

85Station 08

DA17

‐NG‐ST0

8‐08

5MN

MULTI N

etSu

ccess

2017

‐09‐17

T08:08

:47

78.29.54

0 N

017.22

.744

 W59

5.7

2017

‐09‐17

T08:50

:45

78.29.34

6 N

017.24

.785

 W58

7.9

0.34

86Station 08

DA17

‐NG‐ST0

8‐08

6MN

MULTI N

etSu

ccess

2017

‐09‐17

T09:11

:04

78.29.69

4 N

017.20

.838

 W59

9.8

2017

‐09‐17

T09:41

:32

78.29.51

4 N

017.22

.428

 W59

5.8

7.3

87Station 08

DA17

‐NG‐ST0

8‐08

7WP3

WP3

 Net  

Success

2017

‐09‐17

T10:06

:46

78.29.39

0 N

017.23

.790

 W59

9.5

2017

‐09‐17

T10:15

:38

78.29.39

0 N

017.24

.279

 W59

3.8

7.33

88Station 08

DA17

‐NG‐ST0

8‐08

8MN

MULTI N

et 20m

ySu

ccess

2017

‐09‐17

T10:26

:42

78.29.36

8 N

017.24

.911

 W58

8.4

2017

‐09‐17

T10:55

:49

78.29.26

1 N

017.26

.441

 W60

6.9

7.93

89Station 08

DA17

‐NG‐ST0

8‐08

9RRu

moh

r lot 

Success

2017

‐09‐17

T11:24

:13

78.30.05

3 N

017.17

.405

 W58

7.4

2017

‐09‐17

T11:44

:35

78.30.08

0 N

017.18

.436

 W59

4.2

6.97

90Station 08

DA17

‐NG‐ST0

8‐09

0RRu

moh

r lot 

Success

2017

‐09‐17

T11:48

:52

78.30.00

1 N

017.18

.431

 W59

4.9

2017

‐09‐17

T12:08

:38

78.30.00

5 N

017.19

.079

 W59

9.2

6.62

91Station 08

DA17

‐NG‐ST0

8‐09

1RRu

moh

r lot 

Success

2017

‐09‐17

T12:13

:21

78.29.99

4 N

017.19

.166

 W59

9.6

2017

‐09‐17

T12:33

:17

78.30.04

4 N

017.19

.661

 W60

1.5

8.18

92Station 08

DA17

‐NG‐ST0

8‐09

2GGravity corer

Success

2017

‐09‐17

T12:53

:06

78.30.05

4 N

017.16

.711

 W58

2.9

2017

‐09‐17

T13:10

:52

78.30.03

1 N

017.17

.238

 W58

7.3

8.61

93Station 08

DA17

‐NG‐ST0

8‐09

3HAP

SHA

PS  corer

Success

2017

‐09‐17

T13:26

:08

78.29.96

1 N

017.17

.517

 W58

9.8

2017

‐09‐17

T13:45

:49

78.29.96

8 N

017.18

.017

 W59

3.7

8.12

94Station 08

DA17

‐NG‐ST0

8‐09

4HAP

SHA

PS  corer

Success

2017

‐09‐17

T13:48

:58

78.29.99

2 N

017.18

.127

 W59

3.8

2017

‐09‐17

T14:08

:57

78.30.12

9 N

017.18

.755

 W59

4.4

5.42

95Station 08

DA17

‐NG‐ST0

8‐09

5HAP

SHA

PS  corer

Success

2017

‐09‐17

T14:12

:00

78.30.14

5 N

017.18

.834

 W59

3.8

2017

‐09‐17

T14:31

:46

78.30.16

5 N

017.19

.405

 W59

8.3

8.66

96Station 08

DA17

‐NG‐ST0

8‐09

6GGravity corer

Success

2017

‐09‐17

T14:52

:15

78.30.00

7 N

017.21

.527

 W60

220

17‐09‐17

T15:13

:26

78.29.98

4 N

017.21

.874

 W60

1.4

7.13

97Station 08

DA17

‐NG‐ST0

8‐09

7RRu

moh

r lot 

Success

2017

‐09‐17

T15:30

:54

78.29.88

9 N

017.23

.514

 W59

7.3

2017

‐09‐17

T15:50

:51

78.29.77

0 N

017.24

.061

 W59

6.3

9.51

98Station 08

DA17

‐NG‐ST0

8‐09

8RRu

moh

r lot 

Success

2017

‐09‐17

T15:56

:17

78.29.77

5 N

017.24

.256

 W59

4.9

2017

‐09‐17

T16:16

:15

78.29.76

4 N

017.25

.037

 W59

6.1

9.49

99Station 09

DA17

‐NG‐ST0

9‐09

9CTD

SEA (CTD

)Su

ccess

2017

‐09‐17

T21:45

:23

78.14.32

7 N

017.07

.263

 W59

0.2

2017

‐09‐17

T22:45

:38

78.14.46

1 N

017.08

.775

 W59

4.8

9.46

100

Station 09

DA17

‐NG‐ST0

9‐10

0MIK

MIK Net

Success

2017

‐09‐17

T22:58

:34

78.13.97

6 N

017.09

.785

 W60

2.4

2017

‐09‐17

T23:28

:30

78.12.57

4 N

017.11

.835

 W59

9.6

9.89

101

Station 10

DA17

‐NG‐ST1

0‐10

2CTD

SEA (CTD

)Su

ccess

2017

‐09‐18

T06:19

:55

77.56.78

8 N

015.29

.627

 W49

9.1

2017

‐09‐18

T07:12

:44

77.56.56

6 N

015.27

.890

 W49

7.7

6.53

49

Dep

loym

ent 

no.

Statiopn

 no.

Nam

eInstrumen

tStatus

Time Start d

eploym

ent 

(UTC

)Latitud

e Start

Long

itude

 Start

Water dep

th 

Start

timeS

top (UTC

)Latitud

e Stop

Long

itude

 Stop

Water dep

th 

Stop

Wind Sp

eed

102

Station 10

DA17

‐NG‐ST1

0‐xxxTURB

Turbulen

ce  

Fail

2017

‐09‐18

T07:18

:23

77.56.50

8 N

015.27

.598

 W49

7.5

2017

‐09‐18

T07:24

:09

77.56.44

1 N

015.27

.205

 W49

5.4

4.12

103

Station 10

DA17

‐NG‐ST1

0‐10

3TURB

Turbulen

ce  

Success

2017

‐09‐18

T07:28

:50

77.56.35

7 N

015.27

.180

 W49

7.7

2017

‐09‐18

T07:36

:45

77.56.28

4 N

015.27

.095

 W49

3.3

5.5

104

Station 10

DA17

‐NG‐ST1

0‐10

4CTD

SEA (CTD

)Su

ccess

2017

‐09‐18

T07:49

:45

77.56.07

0 N

015.26

.086

 W48

9.1

2017

‐09‐18

T08:05

:40

77.55.98

7 N

015.25

.428

 W48

8.9

6.98

105

Station 10

DA17

‐NG‐ST1

0‐10

5MN

MULTI N

etSu

ccess

2017

‐09‐18

T08:15

:08

77.55.91

0 N

015.24

.848

 W48

9.6

2017

‐09‐18

T08:49

:27

77.55.72

7 N

015.24

.345

 W48

9.7

9.51

106

Station 10

DA17

‐NG‐ST1

0‐10

6MN

MULTI N

etSu

ccess

2017

‐09‐18

T09:14

:01

77.56.85

7 N

015.30

.317

 W50

2.2

2017

‐09‐18

T09:44

:10

77.56.82

7 N

015.29

.046

 W50

4.2

11.78

107

Station 10

DA17

‐NG‐ST1

0‐10

7MN

MULTI N

et 20m

ySu

ccess

2017

‐09‐18

T10:02

:23

77.56.88

4 N

015.28

.883

 W50

3.9

2017

‐09‐18

T10:28

:27

77.56.90

2 N

015.27

.866

 W50

4.9

12.49

108

Station 10

DA17

‐NG‐ST1

0‐10

8RRu

moh

r lot 

Success

2017

‐09‐18

T10:44

:54

77.57.02

7 N

015.30

.384

 W50

420

17‐09‐18

T11:01

:46

77.56.99

1 N

015.29

.885

 W50

3.8

13.47

109

Station 10

DA17

‐NG‐ST1

0‐10

9RRu

moh

r lot 

Success

2017

‐09‐18

T11:08

:33

77.56.98

0 N

015.29

.635

 W50

3.8

2017

‐09‐18

T11:25

:32

77.56.97

1 N

015.29

.097

 W50

416

.51

110

Station 10

DA17

‐NG‐ST1

0‐11

0GGravity corer

Success

2017

‐09‐18

T11:52

:30

77.57.00

5 N

015.30

.512

 W50

3.9

2017

‐09‐18

T12:07

:44

77.57.02

6 N

015.30

.335

 W50

3.7

12.21

111

Station 10

DA17

‐NG‐ST1

0‐11

1HAP

SHA

PS  corer

Success

2017

‐09‐18

T12:24

:34

77.57.05

3 N

015.30

.464

 W50

420

17‐09‐18

T12:41

:29

77.57.05

2 N

015.30

.376

 W50

4.2

11.14

112

Station 10

DA17

‐NG‐ST1

0‐11

2HAP

SHA

PS  corer

Success

2017

‐09‐18

T12:45

:27

77.57.03

9 N

015.30

.451

 W50

420

17‐09‐18

T13:02

:55

77.57.07

9 N

015.29

.995

 W50

4.6

10.6

113

Station 10

DA17

‐NG‐ST1

0‐11

3HAP

SHA

PS  corer

Success

2017

‐09‐18

T13:06

:14

77.57.09

0 N

015.29

.939

 W50

4.5

2017

‐09‐18

T13:23

:50

77.57.11

4 N

015.29

.752

 W50

2.9

9.15

114

Station 10

DA17

‐NG‐ST0

1‐11

4GRu

moh

r lot 

Fail

2017

‐09‐18

T13:37

:29

77.57.05

8 N

015.31

.129

 W50

3.2

2017

‐09‐18

T13:56

:07

77.57.05

5 N

015.30

.790

 W50

3.5

9.06

115

Station 10

DA17

‐NG‐ST1

0‐11

5R 

Rumoh

r lot 

Fail

2017

‐09‐18

T13:56

:47

77.57.05

7 N

015.30

.783

 W50

320

17‐09‐18

T14:14

:33

77.57.09

0 N

015.30

.403

 W50

3.5

8.08

116

Station 10

DA17

‐NG‐ST1

0‐11

6RRu

moh

r lot 

Success

2017

‐09‐18

T14:16

:02

77.57.08

8 N

015.30

.333

 W50

3.4

2017

‐09‐18

T14:33

:39

77.57.09

9 N

015.29

.902

 W50

3.8

8.67

117

Station 10

DA17

‐NG‐ST1

0‐11

7GGravity corer

Success

2017

‐09‐18

T14:56

:49

77.57.51

7 N

015.26

.966

 W49

7.2

2017

‐09‐18

T15:12

:04

77.57.52

7 N

015.26

.504

 W49

8.5

9.46

118

Station 10

DA17

‐NG‐ST1

0‐11

8RRu

moh

r lot 

Fail

2017

‐09‐18

T15:25

:53

77.57.51

7 N

015.25

.567

 W49

3.6

2017

‐09‐18

T15:36

:21

77.57.55

8 N

015.25

.252

 W49

5.1

8.58

119

Station 10

DA17

‐NG‐ST1

0‐11

9RRu

moh

r lot 

Fail

2017

‐09‐18

T15:37

:50

77.57.57

1 N

015.25

.319

 W49

5.4

2017

‐09‐18

T15:47

:55

77.57.64

6 N

015.25

.109

 W49

5.2

12.03

120

Station 10

DA17

‐NG‐ST1

0‐12

0RRu

moh

r lot 

Success

2017

‐09‐18

T15:49

:59

77.57.65

7 N

015.25

.054

 W49

6.8

2017

‐09‐18

T16:07

:07

77.57.76

9 N

015.24

.680

 W49

9.6

11.82

121

Station 10

DA17

‐NG‐ST1

0‐12

1RRu

moh

r lot 

Success

2017

‐09‐18

T16:21

:07

77.57.45

2 N

015.27

.249

 W49

9.1

2017

‐09‐18

T16:39

:05

77.57.64

6 N

015.26

.193

 W49

5.1

10.79

122

Station 11

DA17

‐NG‐ST1

1‐12

2DRG

EDred

ge3

Fail

2017

‐09‐18

T20:51

:49

77.53.21

0 N

013.37

.692

 W34

9.2

2017

‐09‐18

T21:29

:40

77.53.94

9 N

013.32

.156

 W20

3.7

11.67

123

Station 12

DA17

‐NG‐ST1

2‐12

3CTD

SEA (CTD

)Su

ccess

2017

‐09‐18

T23:09

:36

77.45.15

0 N

013.30

.167

 W36

4.9

2017

‐09‐18

T23:59

:58

77.45.33

7 N

013.28

.826

 W36

5.9

11.3

124

Station 12

DA17

‐NG‐ST1

2‐12

4TURB

Turbulen

ce  

Success

2017

‐09‐19

T00:07

:57

77.45.26

6 N

013.27

.967

 W35

9.6

2017

‐09‐19

T00:14

:47

77.45.20

7 N

013.27

.421

 W35

6.7

10.82

125

Station 12

DA17

‐NG‐ST1

2‐12

5CTD

SEA (CTD

)Su

ccess

2017

‐09‐19

T08:27

:34

77.08.07

4 N

010.40

.051

 W49

9.2

2017

‐09‐19

T09:25

:51

77.07.94

2 N

010.40

.750

 W49

8.6

8.66

126

Station 12

DA17

‐NG‐ST1

2‐12

6TURB

Turbulen

ce  

Success

2017

‐09‐19

T09:35

:13

77.07.89

3 N

010.40

.679

 W49

9.8

2017

‐09‐19

T09:44

:19

77.07.76

9 N

010.40

.525

 W50

0.5

7.25

127

Station 12

DA17

‐NG‐ST1

2‐12

7CTD

SEA (CTD

)Su

ccess

2017

‐09‐19

T10:01

:20

77.07.78

2 N

010.40

.544

 W50

0.3

2017

‐09‐19

T10:11

:23

77.07.74

3 N

010.40

.447

 W49

9.8

7.55

128

Station 12

DA17

‐NG‐ST1

2‐12

8MN

MULTI N

etSu

ccess

2017

‐09‐19

T10:19

:08

77.07.68

8 N

010.40

.369

 W49

9.3

2017

‐09‐19

T10:44

:51

77.07.62

8 N

010.40

.527

 W50

1.8

6.66

129

Station 12

DA17

‐NG‐ST1

2‐12

9MN

MULTI N

etSu

ccess

2017

‐09‐19

T11:07

:55

77.08.20

5 N

010.40

.133

 W49

9.2

2017

‐09‐19

T11:30

:41

77.08.23

0 N

010.40

.273

 W50

0.4

6.1

130

Station 12

DA17

‐NG‐ST1

2‐13

0WP3

WP3

 Net  

Success

2017

‐09‐19

T11:38

:59

77.08.21

1 N

010.40

.215

 W49

9.6

2017

‐09‐19

T12:09

:37

77.08.13

5 N

010.39

.846

 W49

8.6

6.73

131

Station 12

DA17

‐NG‐ST1

2‐13

1MN

MULTI N

et 20m

ySu

ccess

2017

‐09‐19

T12:21

:01

77.08.11

8 N

010.39

.696

 W49

8.8

2017

‐09‐19

T12:46

:21

77.08.11

2 N

010.39

.412

 W49

9.6

5.65

132

Station 12

DA17

‐NG‐ST1

2‐13

2RRu

moh

r lot 

Success

2017

‐09‐19

T13:05

:39

77.07.62

6 N

010.40

.812

 W50

1.1

2017

‐09‐19

T13:27

:37

77.07.57

1 N

010.40

.362

 W50

0.1

4.77

133

Station 12

DA17

‐NG‐ST1

2‐13

3RRu

moh

r lot 

Success

2017

‐09‐19

T13:28

:16

77.07.56

9 N

010.40

.351

 W50

0.9

2017

‐09‐19

T13:47

:01

77.07.53

6 N

010.39

.945

 W50

0.5

4.16

134

Station 12

DA17

‐NG‐ST1

2‐13

4RRu

moh

r lot 

Success

2017

‐09‐19

T13:51

:28

77.07.50

3 N

010.39

.792

 W50

0.5

2017

‐09‐19

T14:08

:38

77.07.49

8 N

010.39

.564

 W50

0.6

3.75

135

Station 12

DA17

‐NG‐ST1

2‐13

5GGravity corer

Success

2017

‐09‐19

T14:49

:54

77.07.64

8 N

010.40

.539

 W50

0.9

2017

‐09‐19

T14:49

:55

77.07.65

0 N

010.40

.540

 W50

0.9

4.37

136

Station 12

DA17

‐NG‐ST1

2‐13

6HAP

SHA

PS  corer

Success

2017

‐09‐19

T14:53

:44

77.07.67

9 N

010.40

.579

 W50

0.6

2017

‐09‐19

T15:10

:17

77.07.69

6 N

010.40

.423

 W49

93.3

137

Station 12

DA17

‐NG‐ST1

2‐13

7HAP

SHA

PS  corer

Success

2017

‐09‐19

T15:13

:32

77.07.68

6 N

010.40

.361

 W49

8.7

2017

‐09‐19

T15:30

:09

77.07.64

1 N

010.39

.981

 W50

0.3

3.51

138

Station 12

DA17

‐NG‐ST1

2‐13

8HAP

SHA

PS  corer

Success

2017

‐09‐19

T15:33

:25

77.07.67

8 N

010.39

.951

 W50

0.4

2017

‐09‐19

T15:50

:08

77.07.64

7 N

010.39

.702

 W50

13.18

139

Station 12

DA17

‐NG‐ST1

2‐13

9HAP

SHA

PS  corer

Success

2017

‐09‐19

T15:52

:52

77.07.63

0 N

010.39

.643

 W50

0.7

2017

‐09‐19

T18:46

:21

76.38.45

8 N

011.12

.363

 W31

93.94

140

Station 13

DA17

‐NG‐ST1

3‐14

0CTD

SEA (CTD

)Su

ccess

2017

‐09‐20

T06:34

:03

75.50.87

3 N

012.35

.530

 W39

5.9

2017

‐09‐20

T07:23

:28

75.50.74

2 N

012.36

.105

 W39

97.25

141

Station 13

DA17

‐NG‐ST1

3‐14

1TURB

Turbulen

ce  

Success

2017

‐09‐20

T07:32

:55

75.50.67

2 N

012.36

.562

 W39

8.7

2017

‐09‐20

T07:41

:11

75.50.59

7 N

012.37

.099

 W39

2.8

7.21

142

Station 13

DA17

‐NG‐ST1

3‐14

2CTD

SEA (CTD

)Su

ccess

2017

‐09‐20

T07:50

:30

75.50.50

9 N

012.37

.511

 W38

8.4

2017

‐09‐20

T08:00

:58

75.50.45

4 N

012.37

.379

 W39

1.6

9.19

143

Station 13

DA17

‐NG‐ST1

3‐14

3MN

MULTI N

etFail

2017

‐09‐20

T08:15

:54

75.50.43

6 N

012.36

.896

 W39

4.4

2017

‐09‐20

T08:17

:24

75.50.44

2 N

012.36

.910

 W39

4.4

8.68

144

Station 13

DA17

‐NG‐ST1

3‐14

4MN

MULTI N

etSu

ccess

2017

‐09‐20

T09:01

:56

75.50.19

3 N

012.37

.689

 W38

8.5

2017

‐09‐20

T09:26

:32

75.50.10

7 N

012.37

.888

 W38

8.3

8.48

145

Station 13

DA17

‐NG‐ST1

3‐14

5MN

MULTI N

etSu

ccess

2017

‐09‐20

T09:53

:37

75.49.98

0 N

012.38

.053

 W38

9.6

2017

‐09‐20

T10:13

:12

75.49.89

2 N

012.38

.146

 W39

6.5

8.93

146

Station 13

DA17

‐NG‐ST1

3‐14

6WP3

WP3

 Net  

Success

2017

‐09‐20

T10:20

:30

75.49.85

0 N

012.38

.220

 W39

5.6

2017

‐09‐20

T10:47

:36

75.49.74

6 N

012.38

.173

 W39

3.3

8.21

147

Station 13

DA17

‐NG‐ST1

3‐14

7MN

MULTI N

et 20m

ySu

ccess

2017

‐09‐20

T10:58

:49

75.49.75

1 N

012.37

.975

 W39

4.5

2017

‐09‐20

T11:16

:37

75.49.69

6 N

012.38

.066

 W39

3.2

7.7

148

Station 13

DA17

‐NG‐ST1

3‐14

8RRu

moh

r lot 

Success

2017

‐09‐20

T11:45

:05

75.50.88

9 N

012.35

.586

 W39

7.1

2017

‐09‐20

T11:58

:06

75.50.91

9 N

012.35

.580

 W39

89.2

149

Station 13

DA17

‐NG‐ST1

3‐14

9RRu

moh

r lot 

Success

2017

‐09‐20

T12:01

:33

75.50.89

6 N

012.35

.640

 W39

820

17‐09‐20

T12:14

:52

75.50.92

5 N

012.35

.668

 W39

88.78

150

Station 13

DA17

‐NG‐ST1

3‐15

0RRu

moh

r lot 

Success

2017

‐09‐20

T12:18

:32

75.50.90

8 N

012.35

.716

 W39

8.5

2017

‐09‐20

T12:31

:40

75.50.92

8 N

012.35

.739

 W39

98.65

151

Station 13

DA17

‐NG‐ST1

3‐15

1RRu

moh

r lot 

Success

2017

‐09‐20

T12:35

:08

75.50.91

1 N

012.35

.802

 W39

8.7

2017

‐09‐20

T12:48

:50

75.50.87

8 N

012.35

.604

 W39

7.9

9.1

152

Station 13

DA17

‐NG‐ST1

3‐15

2GGravity corer

Success

2017

‐09‐20

T13:10

:16

75.50.85

9 N

012.35

.523

 W39

7.2

2017

‐09‐20

T13:15

:37

75.50.85

9 N

012.35

.482

 W39

6.9

9.11

153

Station 13

DA17

‐NG‐ST1

3‐15

3HAP

SHA

PS  corer

Success

2017

‐09‐20

T13:28

:58

75.50.86

9 N

012.35

.629

 W39

7.5

2017

‐09‐20

T13:42

:04

75.50.82

6 N

012.35

.583

 W39

8.1

10.65

50

Dep

loym

ent 

no.

Statiopn

 no.

Nam

eInstrumen

tStatus

Time Start d

eploym

ent 

(UTC

)Latitud

e Start

Long

itude

 Start

Water dep

th 

Start

timeS

top (UTC

)Latitud

e Stop

Long

itude

 Stop

Water dep

th 

Stop

Wind Sp

eed

154

Station 13

DA17

‐NG‐ST1

3‐15

4HAP

SHA

PS  corer

Success

2017

‐09‐20

T13:44

:59

75.50.82

3 N

012.35

.540

 W39

7.6

2017

‐09‐20

T13:58

:13

75.50.85

2 N

012.35

.395

 W39

6.6

8.38

155

Station 13

DA17

‐NG‐ST1

3‐15

5HAP

SHA

PS  corer

Success

2017

‐09‐20

T14:01

:12

75.50.85

2 N

012.35

.327

 W39

6.2

2017

‐09‐20

T14:14

:31

75.50.87

9 N

012.35

.113

 W39

5.3

10.13

156

Station 13

DA17

‐NG‐ST1

3‐15

6uCT

DuC

TD 

Success

2017

‐09‐20

T15:10

:57

75.44.34

5 N

013.04

.925

 W25

220

17‐09‐20

T15:18

:29

75.43.35

4 N

013.09

.580

 W25

2.1

5.15

157

Station 13

DA17

‐NG‐ST1

3‐15

7uCT

DuC

TD 

Success

2017

‐09‐20

T15:23

:45

75.42.66

6 N

013.12

.862

 W25

6.3

2017

‐09‐20

T15:30

:30

75.41.79

6 N

013.17

.051

 W25

0.3

9.31

158

Station 14

DA17

‐NG‐ST1

4‐15

8 CT

DSEA (CTD

)Su

ccess

2017

‐09‐21

T06:23

:25

74.05.49

8 N

019.25

.855

 W34

0.4

2017

‐09‐21

T07:08

:17

74.05.77

5 N

019.26

.716

 W34

1.8

9.9

159

Station 14

DA17

‐NG‐ST1

4‐15

9TURB

Turbulen

ce  

Success

2017

‐09‐21

T07:18

:08

74.05.73

9 N

019.26

.971

 W34

120

17‐09‐21

T07:25

:48

74.05.70

6 N

019.27

.346

 W34

1.3

7.62

160

Station 14

DA17

‐NG‐ST1

4‐16

0CTD

SEA (CTD

)Su

ccess

2017

‐09‐21

T07:33

:23

74.05.69

2 N

019.27

.389

 W34

1.9

2017

‐09‐21

T07:47

:13

74.05.65

2 N

019.27

.205

 W34

2.2

6.45

161

Station 14

DA17

‐NG‐ST1

4‐16

1MN

MULTI N

etSu

ccess

2017

‐09‐21

T07:54

:59

74.05.60

3 N

019.27

.192

 W34

1.7

2017

‐09‐21

T08:13

:14

74.05.53

9 N

019.27

.129

 W34

1.6

6.08

162

Station 14

DA17

‐NG‐ST1

4‐16

2MN

MULTI N

etSu

ccess

2017

‐09‐21

T08:30

:43

74.05.47

2 N

019.25

.708

 W33

9.3

2017

‐09‐21

T08:47

:56

74.05.50

7 N

019.25

.702

 W34

0.4

9.1

163

Station 14

DA17

‐NG‐ST1

4‐16

3WP3

WP3

 Net  

Success

2017

‐09‐21

T09:30

:30

74.05.34

1 N

019.25

.936

 W34

0.3

2017

‐09‐21

T09:50

:24

74.05.28

2 N

019.25

.690

 W34

0.5

7.66

164

Station 14

DA17

‐NG‐ST1

4‐16

4MN

MULTI N

et 20m

ySu

ccess

2017

‐09‐21

T10:05

:38

74.05.22

6 N

019.25

.568

 W33

8.2

2017

‐09‐21

T10:21

:40

74.05.23

8 N

019.25

.377

 W33

7.5

7.59

165

Station 14

DA17

‐NG‐ST1

4‐16

5RRu

moh

r lot 

Success

2017

‐09‐21

T10:34

:31

74.05.48

3 N

019.25

.714

 W34

0.1

2017

‐09‐21

T10:45

:01

74.05.46

4 N

019.25

.751

 W34

0.4

8.18

166

Station 14

DA17

‐NG‐ST1

4‐16

6RRu

moh

r lot 

Success

2017

‐09‐21

T10:51

:29

74.05.46

3 N

019.25

.975

 W34

2.4

2017

‐09‐21

T11:02

:48

74.05.46

5 N

019.25

.970

 W34

24.78

167

Station 14

DA17

‐NG‐ST1

4‐16

7RRu

moh

r lot 

Success

2017

‐09‐21

T11:06

:55

74.05.46

9 N

019.25

.983

 W34

2.6

2017

‐09‐21

T11:18

:01

74.05.46

6 N

019.25

.916

 W34

1.7

5.14

168

Station 14

DA17

‐NG‐ST1

4‐16

8RRu

moh

r lot 

Success

2017

‐09‐21

T11:21

:44

74.05.45

3 N

019.25

.901

 W34

1.6

2017

‐09‐21

T11:33

:19

74.05.44

9 N

019.25

.959

 W34

1.4

7.59

169

Station 14

DA17

‐NG‐ST1

4‐16

9RRu

moh

r lot 

Fail

2017

‐09‐21

T11:37

:23

74.05.42

9 N

019.25

.977

 W34

1.5

2017

‐09‐21

T11:50

:47

74.05.41

5 N

019.25

.928

 W34

1.1

9.11

170

Station 14

DA17

‐NG‐ST1

4‐17

0RRu

moh

r lot 

Success

2017

‐09‐21

T11:51

:11

74.05.41

4 N

019.25

.935

 W34

1.3

2017

‐09‐21

T12:02

:16

74.05.42

9 N

019.26

.070

 W34

28.42

171

Station 14

DA17

‐NG‐ST1

4‐17

1GGravity corer

Success

2017

‐09‐21

T12:20

:14

74.05.41

3 N

019.25

.862

 W34

1.2

2017

‐09‐21

T12:32

:24

74.05.41

7 N

019.25

.860

 W34

1.3

6.13

172

Station 14

DA17

‐NG‐ST1

4‐17

2RRu

moh

r lot 

Success

2017

‐09‐21

T12:42

:51

74.05.40

6 N

019.25

.821

 W34

1.4

2017

‐09‐21

T12:54

:02

74.05.44

7 N

019.25

.908

 W34

1.5

7.8

173

Station 14

DA17

‐NG‐ST1

4‐17

3RRu

moh

r lot 

Success

2017

‐09‐21

T12:59

:10

74.05.44

0 N

019.25

.957

 W34

1.8

2017

‐09‐21

T13:09

:20

74.05.45

0 N

019.25

.968

 W34

2.4

8.6

174

Station 14

DA17

‐NG‐ST1

4‐17

4HAP

SHA

PS  corer

Success

2017

‐09‐21

T13:15

:54

74.05.45

2 N

019.25

.955

 W34

220

17‐09‐21

T13:27

:10

74.05.44

9 N

019.25

.947

 W34

2.3

8.24

175

Station 14

DA17

‐NG‐ST1

4‐17

5HAP

SHA

PS  corer

Success

2017

‐09‐21

T13:39

:45

74.05.46

3 N

019.25

.853

 W34

1.6

2017

‐09‐21

T13:51

:10

74.05.44

5 N

019.25

.783

 W34

0.4

8.59

176

Station 14

DA17

‐NG‐ST1

4‐17

6HAP

SHA

PS  corer

Success

2017

‐09‐21

T13:54

:34

74.05.45

3 N

019.25

.699

 W34

0.5

2017

‐09‐21

T14:05

:57

74.05.40

9 N

019.25

.773

 W34

1.5

8.63

177

Station 14

DA17

‐NG‐ST1

4‐17

7HAP

SHA

PS  corer

Success

2017

‐09‐21

T14:08

:55

74.05.39

6 N

019.25

.800

 W34

0.8

2017

‐09‐21

T14:20

:06

74.05.34

8 N

019.25

.925

 W34

1.3

8.7

178

Station 14

DA17

‐NG‐ST1

4‐17

8MO

Moo

ring

Success

2017

‐09‐21

T15:35

:48

74.05.63

4 N

019.08

.632

 W27

3.2

2017

‐09‐21

T15:35

:51

74.05.64

8 N

019.08

.618

 W27

1.9

11.27

179

Station 15

DA17

‐NG‐ST1

5‐17

9CTD

SEA (CTD

)Su

ccess

2017

‐09‐21

T16:26

:46

74.12.38

6 N

019.01

.592

 W14

5.5

2017

‐09‐21

T16:46

:00

74.12.16

2 N

019.01

.520

 W14

5.8

8.95

180

Station 15

DA17

‐NG‐ST1

5‐18

0GGravity corer

Success

2017

‐09‐21

T17:02

:02

74.12.46

5 N

019.01

.947

 W14

3.8

2017

‐09‐21

T17:06

:36

74.12.42

7 N

019.01

.938

 W14

59.63

181

Station 15

DA17

‐NG‐ST1

5‐18

1RRu

moh

r lot 

Success

2017

‐09‐21

T17:20

:34

74.12.35

6 N

019.01

.920

 W14

3.8

2017

‐09‐21

T17:30

:22

74.12.30

9 N

019.02

.028

 W14

6.7

9.73

182

Station 15

DA17

‐NG‐ST1

5‐18

2RRu

moh

r lot 

Success

2017

‐09‐21

T17:39

:50

74.12.24

2 N

019.02

.051

 W14

9.4

2017

‐09‐21

T17:39

:52

74.12.24

2 N

019.02

.051

 W14

9.4

11.1

183

Station 16

DA17

‐NG‐ST1

6‐18

3MIK

MIK Net

Success

2017

‐09‐22

T05:33

:14

74.21.16

6 N

020.18

.925

 W16

8.7

2017

‐09‐22

T05:57

:04

74.20.01

9 N

020.18

.340

 W16

6.1

7.04

184

Station 16

DA17

‐NG‐ST1

6‐18

4CTD

SEA (CTD

)Su

ccess

2017

‐09‐22

T06:29

:54

74.18.46

8 N

020.17

.765

 W15

7.9

2017

‐09‐22

T07:03

:25

74.18.46

8 N

020.17

.810

 W15

7.5

8.46

185

Station 16

DA17

‐NG‐ST1

6‐18

5TURB

Turbulen

ce  

Success

2017

‐09‐22

T07:14

:20

74.18.35

1 N

020.17

.881

 W15

420

17‐09‐22

T07:20

:51

74.18.24

7 N

020.17

.854

 W15

3.7

6.5

186

Station 16

DA17

‐NG‐ST1

6‐18

6CTD

SEA (CTD

)Su

ccess

2017

‐09‐22

T07:34

:14

74.18.35

7 N

020.17

.777

 W15

6.9

2017

‐09‐22

T07:43

:07

74.18.32

7 N

020.17

.633

 W15

7.3

9.04

187

Station 16

DA17

‐NG‐ST1

6‐18

7MN

MULTI N

etSu

ccess

2017

‐09‐22

T07:51

:51

74.18.26

3 N

020.17

.311

 W14

8.3

2017

‐09‐22

T07:59

:13

74.18.29

1 N

020.17

.311

 W14

5.2

11.15

188

Station 16

DA17

‐NG‐ST1

6‐18

8MN

MULTI N

etSu

ccess

2017

‐09‐22

T08:17

:37

74.18.46

2 N

020.17

.747

 W15

7.7

2017

‐09‐22

T08:26

:35

74.18.40

4 N

020.17

.873

 W15

75.84

189

Station 16

DA17

‐NG‐ST1

6‐18

9WP3

WP3

 Net  

Success

2017

‐09‐22

T08:40

:58

74.18.42

2 N

020.17

.788

 W15

7.6

2017

‐09‐22

T08:55

:19

74.18.43

9 N

020.17

.380

 W15

2.7

4.29

190

Station 16

DA17

‐NG‐ST1

6‐19

0MN

MULTI N

et 20m

ySu

ccess

2017

‐09‐22

T09:03

:45

74.18.45

0 N

020.17

.195

 W14

7.5

2017

‐09‐22

T09:11

:41

74.18.49

6 N

020.17

.065

 W13

34.27

191

Station 16

DA17

‐NG‐ST1

6‐19

1RRu

moh

r lot 

Success

2017

‐09‐22

T10:24

:11

74.18.52

1 N

020.17

.599

 W15

7.4

2017

‐09‐22

T10:29

:32

74.18.49

3 N

020.17

.700

 W15

8.5

12.12

192

Station 16

DA17

‐NG‐ST1

6‐19

2RRu

moh

r lot 

Success

2017

‐09‐22

T10:32

:10

74.18.50

4 N

020.17

.672

 W15

8.7

2017

‐09‐22

T10:37

:32

74.18.53

7 N

020.17

.625

 W15

6.3

10.63

193

Station 16

DA17

‐NG‐ST1

6‐19

3RRu

moh

r lot 

Success

2017

‐09‐22

T10:40

:07

74.18.54

9 N

020.17

.582

 W15

4.9

2017

‐09‐22

T10:45

:34

74.18.55

2 N

020.17

.617

 W15

5.7

14.5

194

Station 16

DA17

‐NG‐ST1

6‐19

4RRu

moh

r lot 

Success

2017

‐09‐22

T10:49

:26

74.18.51

6 N

020.17

.704

 W15

8.9

2017

‐09‐22

T10:54

:47

74.18.51

6 N

020.17

.742

 W15

8.6

11.02

195

Station 16

DA17

‐NG‐ST1

6‐19

5RRu

moh

r lot 

Success

2017

‐09‐22

T10:57

:45

74.18.53

3 N

020.17

.707

 W15

8.8

2017

‐09‐22

T11:03

:07

74.18.53

9 N

020.17

.707

 W15

8.8

12.05

196

Station 16

DA17

‐NG‐ST1

6‐19

6RRu

moh

r lot 

Success

2017

‐09‐22

T11:07

:44

74.18.51

1 N

020.17

.798

 W15

920

17‐09‐22

T11:13

:01

74.18.52

0 N

020.17

.714

 W15

910

.22

197

Station 16

DA17

‐NG‐ST1

6‐19

7RRu

moh

r lot 

Success

2017

‐09‐22

T11:17

:18

74.18.53

2 N

020.17

.799

 W15

9.2

2017

‐09‐22

T11:22

:43

74.18.52

8 N

020.17

.955

 W15

913

.28

198

Station 16

DA17

‐NG‐ST1

6‐19

8RRu

moh

r lot 

Success

2017

‐09‐22

T11:23

:51

74.18.54

0 N

020.17

.962

 W15

920

17‐09‐22

T11:31

:38

74.18.57

8 N

020.17

.946

 W15

9.4

11.1

199

Station 16

DA17

‐NG‐ST1

6‐19

9RRu

moh

r lot 

Fail

2017

‐09‐22

T12:03

:48

74.18.55

4 N

020.18

.004

 W15

9.7

2017

‐09‐22

T12:03

:57

74.18.55

4 N

020.18

.009

 W15

9.7

11.48

200

Station 16

DA17

‐NG‐ST1

6‐20

0RRu

moh

r lot 

Success

2017

‐09‐22

T12:05

:32

74.18.54

4 N

020.18

.064

 W15

9.2

2017

‐09‐22

T12:10

:55

74.18.54

2 N

020.18

.166

 W15

8.8

8.56

201

Station 16

DA17

‐NG‐ST1

6‐20

1RRu

moh

r lot 

Success

2017

‐09‐22

T12:13

:22

74.18.54

7 N

020.18

.132

 W15

8.9

2017

‐09‐22

T12:20

:07

74.18.55

0 N

020.17

.958

 W15

9.6

10.07

202

Station 16

DA17

‐NG‐ST1

6‐20

2RRu

moh

r lot 

Success

2017

‐09‐22

T12:24

:27

74.18.55

2 N

020.17

.848

 W15

9.4

2017

‐09‐22

T12:29

:42

74.18.55

9 N

020.17

.780

 W15

9.6

6.19

203

Station 16

DA17

‐NG‐ST1

6‐20

3GGravity corer

Success

2017

‐09‐22

T12:54

:27

74.18.50

8 N

020.17

.526

 W15

7.8

2017

‐09‐22

T12:59

:35

74.18.52

4 N

020.17

.482

 W15

6.8

8.04

204

Station 16

DA17

‐NG‐ST1

6‐20

4HAP

SHA

PS  corer

Success

2017

‐09‐22

T13:38

:29

74.18.54

3 N

020.17

.515

 W15

6.7

2017

‐09‐22

T13:44

:51

74.18.54

5 N

020.17

.425

 W15

3.4

12.96

205

Station 16

DA17

‐NG‐ST1

6‐20

5HAP

SHA

PS  corer

Success

2017

‐09‐22

T13:46

:36

74.18.51

7 N

020.17

.422

 W15

4.8

2017

‐09‐22

T13:53

:11

74.18.49

1 N

020.17

.403

 W15

6.2

10.66

51

Dep

loym

ent 

no.

Statiopn

 no.

Nam

eInstrumen

tStatus

Time Start d

eploym

ent 

(UTC

)Latitud

e Start

Long

itude

 Start

Water dep

th 

Start

timeS

top (UTC

)Latitud

e Stop

Long

itude

 Stop

Water dep

th 

Stop

Wind Sp

eed

206

Station 16

DA17

‐NG‐ST1

6‐20

6HAP

SHA

PS  corer

Success

2017

‐09‐22

T13:55

:49

74.18.46

7 N

020.17

.452

 W15

7.2

2017

‐09‐22

T14:04

:03

74.18.45

7 N

020.17

.702

 W15

8.9

11.95

207

Station 16

DA17

‐NG‐ST1

6‐20

7HAP

SHA

PS  corer

Success

2017

‐09‐22

T14:04

:47

74.18.45

4 N

020.17

.737

 W15

920

17‐09‐22

T14:12

:24

74.18.42

6 N

020.18

.057

 W15

4.4

11.35

208A

Station 16

FAILED

Rumoh

r lot 

Fail

2017

‐09‐22

T14:23

:53

74.18.52

0 N

020.17

.703

 W15

9.6

2017

‐09‐22

T14:31

:34

74.18.48

2 N

020.17

.990

 W15

8.1

11.36

208B

Station 16

DA17

‐NG‐ST1

6‐20

8RRu

moh

r lot 

Fail

2017

‐09‐22

T14:xx:xx

74.18.52

0 N

020.17

.703

 W15

9.6

2017

‐09‐22

T14:xx:xx

74.18.48

2 N

020.17

.990

 W15

8.1

‐20

9Station 16

DA17

‐NG‐ST1

6‐20

9RRu

moh

r lot 

Fail

2017

‐09‐22

T14:32

:23

74.18.47

9 N

020.18

.027

 W15

8.1

2017

‐09‐22

T14:36

:47

74.18.46

9 N

020.18

.142

 W15

6.8

10.61

210

Station 16

DA17

‐NG‐ST1

6‐21

0GC

Gravity corer

Success

2017

‐09‐22

T15:30

:26

74.18.45

5 N

020.17

.762

 W15

8.9

2017

‐09‐22

T15:56

:30

74.18.40

3 N

020.15

.713

 W47

.712

.15

211

Station 17

DA17

‐NG‐ST1

7‐21

1VV

Van Ve

en Grab

Success

2017

‐09‐22

T16:20

:35

74.18.46

1 N

020.15

.360

 W38

.520

17‐09‐22

T16:23

:01

74.18.44

9 N

020.15

.299

 W35

.611

.48

212

Station 17

DA17

‐NG‐ST1

7‐21

2VV

Van Ve

en Grab

Success

2017

‐09‐22

T16:33

:11

74.18.41

0 N

020.15

.651

 W46

.520

17‐09‐22

T16:36

:39

74.18.39

3 N

020.15

.423

 W40

.813

.221

3Station 18

DA17

‐NG‐ST1

8‐21

3 G

Gravity corer

Success

2017

‐09‐22

T17:23

:14

74.20.94

5 N

020.20

.299

 W16

8.1

2017

‐09‐22

T17:23

:20

74.20.94

4 N

020.20

.298

 W16

8.1

12.11

214

Station 18

DA17

‐NG‐ST1

8‐21

4 R

Rumoh

r lot 

Success

2017

‐09‐22

T17:35

:52

74.20.95

7 N

020.20

.400

 W16

7.5

2017

‐09‐22

T17:52

:23

74.20.94

5 N

020.20

.270

 W16

812

.04

215

Station 18

DA17

‐NG‐ST1

8‐21

5RRu

moh

r lot 

Success

2017

‐09‐22

T17:55

:55

74.20.92

8 N

020.20

.229

 W16

8.2

2017

‐09‐22

T18:01

:22

74.20.91

0 N

020.20

.143

 W16

8.2

14.21

216

Station 18

DA17

‐NG‐ST1

8‐21

6RRu

moh

r lot 

Success

2017

‐09‐22

T18:05

:12

74.20.95

1 N

020.20

.122

 W16

8.3

2017

‐09‐22

T18:10

:55

74.20.93

1 N

020.20

.153

 W16

8.2

11.36

217

Station 18

DA17

‐NG‐ST1

8‐21

7uCT

DuC

TD 

Success

2017

‐09‐22

T18:36

:04

74.22.18

7 N

020.23

.319

 W94

2017

‐09‐22

T22:10

:50

74.25.07

9 N

021.39

.711

 W14

9.6

3.12

218

Station 19

DA17

‐NG‐ST1

9‐21

8MIK

MIK Net

Success

2017

‐09‐23

T05:03

:56

74.26.51

4 N

021.29

.105

 W28

8.6

2017

‐09‐23

T05:38

:24

74.27.01

3 N

021.23

.858

 W33

0.4

11.48

219

Station 19

DA17

‐NG‐ST1

9‐21

9CTD

SEA (CTD

)Su

ccess

2017

‐09‐23

T06:13

:11

74.27.85

6 N

021.11

.314

 W33

220

17‐09‐23

T06:57

:53

74.27.79

8 N

021.11

.633

 W33

25.87

220

Station 19

DA17

‐NG‐ST1

9‐22

0TURB

Turbulen

ce  

Success

2017

‐09‐23

T07:05

:51

74.27.78

0 N

021.11

.811

 W33

1.9

2017

‐09‐23

T07:13

:53

74.27.80

7 N

021.12

.101

 W33

1.9

5.93

221

Station 19

DA17

‐NG‐ST1

9‐22

1CTD

SEA (CTD

)Su

ccess

2017

‐09‐23

T07:30

:24

74.27.75

3 N

021.12

.107

 W33

1.7

2017

‐09‐23

T07:39

:40

74.27.71

8 N

021.12

.170

 W33

1.3

7.21

222

Station 19

DA17

‐NG‐ST1

9‐22

2MN

MULTI N

etSu

ccess

2017

‐09‐23

T07:50

:02

74.27.73

3 N

021.12

.241

 W33

1.5

2017

‐09‐23

T08:08

:09

74.27.75

2 N

021.12

.418

 W33

1.5

7.56

223

Station 19

DA17

‐NG‐ST1

9‐22

3MN

MULTI N

etSu

ccess

2017

‐09‐23

T08:27

:08

74.27.83

6 N

021.11

.531

 W33

1.8

2017

‐09‐23

T08:43

:39

74.27.80

3 N

021.11

.558

 W33

1.9

6.67

224

Station 19

DA17

‐NG‐ST1

9‐22

4WP3

WP3

 Net  

Success

2017

‐09‐23

T08:55

:53

74.27.75

7 N

021.11

.581

 W33

220

17‐09‐23

T09:07

:26

74.27.72

7 N

021.11

.675

 W33

1.9

6.08

225

Station 19

DA17

‐NG‐ST1

9‐22

5MN

MULTI N

et 20m

ySu

ccess

2017

‐09‐23

T09:18

:28

74.27.68

7 N

021.11

.491

 W32

8.3

2017

‐09‐23

T09:34

:31

74.27.64

1 N

021.11

.350

 W31

5.7

6.76

226

Station 19

DA17

‐NG‐ST1

9‐22

6RRu

moh

r lot 

Success

2017

‐09‐23

T10:20

:53

74.27.78

5 N

021.11

.296

 W33

2.2

2017

‐09‐23

T10:28

:22

74.27.77

8 N

021.11

.355

 W33

2.3

5.78

227

Station 19

DA17

‐NG‐ST1

9‐22

7RRu

moh

r lot 

Success

2017

‐09‐23

T10:31

:51

74.27.77

5 N

021.11

.322

 W33

2.3

2017

‐09‐23

T10:42

:54

74.27.80

9 N

021.11

.415

 W33

2.4

6.6

228

Station 19

DA17

‐NG‐ST1

9‐22

8RRu

moh

r lot 

Success

2017

‐09‐23

T10:46

:00

74.27.81

4 N

021.11

.494

 W33

2.4

2017

‐09‐23

T10:56

:44

74.27.80

6 N

021.11

.419

 W33

2.4

5.76

229

Station 19

DA17

‐NG‐ST1

9‐22

9RRu

moh

r lot 

Success

2017

‐09‐23

T11:00

:45

74.27.80

1 N

021.11

.419

 W33

2.5

2017

‐09‐23

T11:11

:39

74.27.78

8 N

021.11

.555

 W33

2.6

3.76

230

Station 19

DA17

‐NG‐ST1

9‐23

0RRu

moh

r lot 

Success

2017

‐09‐23

T11:17

:14

74.27.78

2 N

021.11

.416

 W33

2.6

2017

‐09‐23

T11:32

:06

74.27.79

3 N

021.11

.386

 W33

2.7

4.24

231

Station 19

DA17

‐NG‐ST1

9‐23

1RRu

moh

r lot 

Success

2017

‐09‐23

T11:37

:27

74.27.79

2 N

021.11

.386

 W33

2.7

2017

‐09‐23

T11:48

:19

74.27.79

3 N

021.11

.511

 W33

2.8

4.18

232

Station 19

DA17

‐NG‐ST1

9‐23

2RRu

moh

r lot 

Success

2017

‐09‐23

T11:52

:27

74.27.78

2 N

021.11

.475

 W33

2.8

2017

‐09‐23

T12:03

:51

74.27.78

5 N

021.11

.641

 W33

2.9

3.59

233

Station 19

DA17

‐NG‐ST1

9‐23

3RRu

moh

r lot 

Success

2017

‐09‐23

T12:07

:11

74.27.79

3 N

021.11

.731

 W33

2.9

2017

‐09‐23

T12:18

:05

74.27.77

9 N

021.11

.703

 W33

33.35

234

Station 19

DA17

‐NG‐ST1

9‐23

4RRu

moh

r lot 

Success

2017

‐09‐23

T12:19

:03

74.27.77

7 N

021.11

.706

 W33

320

17‐09‐23

T12:29

:55

74.27.75

2 N

021.11

.677

 W33

32.28

235

Station 19

DA17

‐NG‐ST1

9‐23

5GGravity corer

Success

2017

‐09‐23

T12:49

:28

74.27.78

8 N

021.11

.450

 W33

3.1

2017

‐09‐23

T12:59

:37

74.27.77

2 N

021.11

.401

 W33

3.1

3.77

236

Station 19

DA17

‐NG‐ST1

9‐23

6HAP

SHA

PS  corer

Success

2017

‐09‐23

T13:28

:20

74.27.83

2 N

021.11

.459

 W33

320

17‐09‐23

T13:39

:24

74.27.84

6 N

021.11

.590

 W33

34.22

237

Station 19

DA17

‐NG‐ST1

9‐23

7HAP

SHA

PS  corer

Success

2017

‐09‐23

T13:48

:22

74.27.84

4 N

021.11

.673

 W33

3.1

2017

‐09‐23

T13:59

:29

74.27.83

7 N

021.11

.908

 W33

3.1

3.04

238

Station 19

DA17

‐NG‐ST1

9‐23

8HAP

SHA

PS  corer

Success

2017

‐09‐23

T14:02

:10

74.27.83

7 N

021.12

.008

 W33

3.1

2017

‐09‐23

T14:13

:03

74.27.84

3 N

021.12

.152

 W33

3.2

3.18

239

Station 19

DA17

‐NG‐ST1

9‐23

9HAP

SHA

PS  corer

Success

2017

‐09‐23

T14:15

:25

74.27.84

9 N

021.12

.221

 W33

3.2

2017

‐09‐23

T14:26

:35

74.27.87

9 N

021.12

.279

 W33

3.1

2.56

240

Station 19

DA17

‐NG‐ST1

9‐24

0HAP

SHA

PS  corer

Success

2017

‐09‐23

T14:29

:02

74.27.88

9 N

021.12

.386

 W33

320

17‐09‐23

T14:40

:08

74.27.89

4 N

021.12

.388

 W33

33.77

241

Station 19

DA17

‐NG‐ST1

9‐24

1uCT

DuC

TD 

Success

2017

‐09‐23

T14:49

:22

74.27.63

8 N

021.15

.239

 W30

5.7

2017

‐09‐23

T15:46

:07

74.26.24

7 N

021.42

.709

 W15

15

242

Station 20

DA17

‐NG‐ST2

0‐24

2CTD

SEA (CTD

)Su

ccess

2017

‐09‐23

T17:19

:08

74.27.36

4 N

020.59

.566

 W27

9.7

2017

‐09‐23

T17:45

:13

74.27.31

7 N

020.59

.756

 W28

72.79

243

Station 21

DA17

‐NG‐ST2

1‐24

3RRu

moh

r lot 

Success

2017

‐09‐23

T18:40

:17

74.25.28

6 N

020.30

.337

 W14

6.5

2017

‐09‐23

T18:45

:06

74.25.31

1 N

020.30

.384

 W14

7.5

6.71

244

Station 21

DA17

‐NG‐ST2

1‐24

4RRu

moh

r lot 

Success

2017

‐09‐23

T18:48

:03

74.25.32

8 N

020.30

.448

 W15

0.2

2017

‐09‐23

T18:53

:24

74.25.34

3 N

020.30

.574

 W15

4.2

7.08

245

Station 21

DA17

‐NG‐ST2

1‐24

5GGravity corer

Success

2017

‐09‐23

T19:10

:31

74.25.40

8 N

020.30

.893

 W15

6.5

2017

‐09‐23

T19:10

:42

74.25.40

9 N

020.30

.899

 W15

6.5

7.56

246

Station 16

DA17

‐NG‐ST1

6‐24

6HAP

SHA

PS  corer

Success

2017

‐09‐23

T20:10

:36

74.18.62

8 N

020.17

.957

 W15

8.8

2017

‐09‐23

T20:15

:29

74.18.60

4 N

020.17

.982

 W15

8.9

2.72

247

Station 22

DA17

‐NG‐ST2

2‐24

1uCT

DuC

TD 

Success

2017

‐09‐23

T20:31

:07

74.17.48

9 N

020.18

.514

 W88

.120

17‐09‐23

T21:25

:57

74.12.45

7 N

019.59

.256

 W17

9.9

4.43

248

Station 22

DA17

‐NG‐ST2

2‐24

8MIK

MIK Net

Success

2017

‐09‐24

T04:11

:53

74.26.21

9 N

018.45

.228

 W12

8.4

2017

‐09‐24

T04:52

:12

74.24.85

4 N

018.50

.518

 W14

57.11

249

Station 22

DA17

‐NG‐ST2

2‐24

9CTD

SEA (CTD

)Su

ccess

2017

‐09‐24

T05:19

:56

74.26.67

2 N

018.43

.009

 W14

3.9

2017

‐09‐24

T05:49

:21

74.26.60

2 N

018.42

.594

 W14

28.48

250

Station 22

DA17

‐NG‐ST2

2‐25

0TURB

Turbulen

ce  

Success

2017

‐09‐24

T06:01

:57

74.26.68

6 N

018.42

.348

 W13

6.8

2017

‐09‐24

T06:08

:44

74.26.61

3 N

018.42

.683

 W13

9.7

9.03

251

Station 22

DA17

‐NG‐ST2

2‐25

1CTD

SEA (CTD

)Su

ccess

2017

‐09‐24

T06:15

:26

74.26.58

9 N

018.43

.162

 W14

720

17‐09‐24

T06:23

:46

74.26.53

4 N

018.43

.146

 W14

5.7

10.03

252

Station 22

DA17

‐NG‐ST2

2‐25

2GGravity corer

Success

2017

‐09‐24

T06:54

:11

74.26.57

5 N

018.43

.130

 W14

7.1

2017

‐09‐24

T06:54

:17

74.26.57

4 N

018.43

.125

 W14

5.6

13.35

253

Station 22

DA17

‐NG‐ST2

2‐25

3RRu

moh

r lot 

Success

2017

‐09‐24

T07:20

:13

74.26.62

6 N

018.43

.317

 W14

6.8

2017

‐09‐24

T07:33

:46

74.26.56

0 N

018.43

.006

 W14

3.8

12.9

254

Station 22

DA17

‐NG‐ST2

2‐25

4RRu

moh

r lot 

Success

2017

‐09‐24

T07:37

:47

74.26.52

0 N

018.42

.872

 W14

4.6

2017

‐09‐24

T07:43

:07

74.26.50

4 N

018.42

.788

 W14

5.8

12.3

255

Station 22

DA17

‐NG‐ST2

2‐25

5RRu

moh

r lot 

Fail

2017

‐09‐24

T07:51

:28

74.26.75

0 N

018.43

.730

 W14

520

17‐09‐24

T07:56

:45

74.26.69

7 N

018.43

.497

 W14

7.7

10.9

256

Station 22

DA17

‐NG‐ST2

2‐25

6RRu

moh

r lot 

Success

2017

‐09‐24

T07:59

:47

74.26.67

1 N

018.43

.344

 W14

6.2

2017

‐09‐24

T08:05

:04

74.26.67

0 N

018.43

.272

 W14

5.9

14.1

52

Dep

loym

ent 

no.

Statiopn

 no.

Nam

eInstrumen

tStatus

Time Start d

eploym

ent 

(UTC

)Latitud

e Start

Long

itude

 Start

Water dep

th 

Start

timeS

top (UTC

)Latitud

e Stop

Long

itude

 Stop

Water dep

th 

Stop

Wind Sp

eed

257

Station 22

DA17

‐NG‐ST2

2‐25

7HAP

SHA

PS  corer

Success

2017

‐09‐24

T08:13

:53

74.26.66

6 N

018.43

.324

 W14

6.2

2017

‐09‐24

T08:19

:05

74.26.67

7 N

018.43

.435

 W14

7.1

11.44

258

Station 22

DA17

‐NG‐ST2

2‐25

8HAP

SHA

PS  corer

Success

2017

‐09‐24

T08:21

:55

74.26.66

3 N

018.43

.540

 W14

6.9

2017

‐09‐24

T08:27

:15

74.26.66

6 N

018.43

.643

 W14

7.1

16.4

259

Station 22

DA17

‐NG‐ST2

2‐25

9HAP

SHA

PS  corer

Success

2017

‐09‐24

T08:31

:41

74.26.61

9 N

018.43

.633

 W14

5.6

2017

‐09‐24

T08:36

:39

74.26.62

4 N

018.43

.593

 W14

6.3

13.61

260

Station 22

DA17

‐NG‐ST2

2‐26

0MN

MULTI N

etSu

ccess

2017

‐09‐24

T09:00

:40

74.26.62

6 N

018.43

.585

 W14

6.6

2017

‐09‐24

T09:08

:41

74.26.62

2 N

018.43

.667

 W14

6.4

13.65

261

Station 15

DA17

‐NG‐ST1

5‐26

1RRu

moh

r lot 

Fail

2017

‐09‐24

T10:57

:43

74.12.65

9 N

019.01

.008

 W14

6.8

2017

‐09‐24

T11:09

:50

74.12.62

6 N

019.01

.230

 W14

6.3

21.72

262

Station 23

DA17

‐NG‐ST2

3‐26

2CTD

SEA (CTD

)Su

ccess

2017

‐09‐25

T06:05

:00

74.07.48

8 N

019.25

.553

 W30

0.1

2017

‐09‐25

T06:47

:46

74.06.80

9 N

019.27

.137

 W31

3.1

8.65

263

Station 24

DA17

‐NG‐ST2

4‐26

3CTD

SEA (CTD

)Su

ccess

2017

‐09‐25

T08:26

:04

73.59.85

4 N

018.45

.345

 W37

4.3

2017

‐09‐25

T09:12

:15

73.59.77

0 N

018.46

.227

 W28

1.2

12.65

264

Station 24

DA17

‐NG‐ST2

4‐26

0uCT

DuC

TD 

Success

2017

‐09‐25

T09:24

:34

73.59.00

8 N

018.42

.199

 W25

7.4

2017

‐09‐25

T09:29

:47

73.58.52

0 N

018.39

.573

 W28

5.9

9.1

265

Station 24

DA17

‐NG‐ST2

4‐26

5uCT

DuC

TD 

Success

2017

‐09‐25

T09:37

:17

73.57.81

4 N

018.35

.835

 W32

8.1

2017

‐09‐25

T09:43

:39

73.57.19

7 N

018.32

.700

 W33

3.6

11.79

266

Station 24

DA17

‐NG‐ST2

4‐26

6uCT

DuC

TD 

Success

2017

‐09‐25

T09:48

:56

73.56.67

7 N

018.30

.226

 W33

5.3

2017

‐09‐25

T09:55

:58

73.55.96

9 N

018.26

.943

 W34

4.5

12.89

267

Station 24

DA17

‐NG‐ST2

4‐26

7uCT

DuC

TD 

Success

2017

‐09‐25

T10:01

:41

73.55.41

2 N

018.24

.311

 W34

920

17‐09‐25

T10:08

:49

73.54.75

3 N

018.20

.947

 W35

1.1

11.86

268

Station 24

DA17

‐NG‐ST2

4‐26

8uCT

DuC

TD 

Success

2017

‐09‐25

T10:14

:13

73.54.36

9 N

018.19

.131

 W34

9.6

2017

‐09‐25

T10:20

:44

73.53.95

4 N

018.17

.144

 W34

6.5

11.37

269

Station 24

DA17

‐NG‐ST2

4‐26

9uCT

DuC

TD 

Success

2017

‐09‐25

T10:26

:55

73.53.55

0 N

018.15

.280

 W34

5.6

2017

‐09‐25

T10:32

:53

73.53.14

9 N

018.13

.484

 W35

6.4

9.46

270

Station 25

DA17

‐NG‐ST2

5‐27

0CTD

SEA (CTD

)Su

ccess

2017

‐09‐25

T11:04

:37

73.51.80

6 N

018.06

.068

 W33

9.7

2017

‐09‐25

T11:48

:54

73.51.50

2 N

018.07

.591

 W32

7.2

6.9

271

Station 25

DA17

‐NG‐ST2

5‐27

1uCT

DuC

TD 

Success

2017

‐09‐25

T12:05

:10

73.50.89

3 N

018.04

.868

 W31

9.2

2017

‐09‐25

T12:10

:36

73.50.58

2 N

018.03

.694

 W31

57.42

272

Station 25

DA17

‐NG‐ST2

5‐27

2uCT

DuC

TD 

Success

2017

‐09‐25

T12:15

:06

73.50.29

7 N

018.02

.394

 W31

2.4

2017

‐09‐25

T12:21

:24

73.49.89

8 N

018.00

.368

 W31

1.5

7.13

273

Station 25

DA17

‐NG‐ST2

5‐27

3uCT

DuC

TD 

Success

2017

‐09‐25

T12:25

:48

73.49.61

8 N

017.59

.002

 W30

9.2

2017

‐09‐25

T12:31

:45

73.49.24

3 N

017.57

.065

 W31

9.8

7.82

274

Station 25

DA17

‐NG‐ST2

5‐27

4uCT

DuC

TD 

Success

2017

‐09‐25

T12:36

:53

73.48.96

0 N

017.55

.524

 W30

4.5

2017

‐09‐25

T12:42

:32

73.48.65

5 N

017.53

.871

 W30

0.2

7.83

275

Station 25

DA17

‐NG‐ST2

5‐27

5uCT

DuC

TD 

Success

2017

‐09‐25

T12:48

:07

73.48.32

9 N

017.52

.070

 W30

4.5

2017

‐09‐25

T12:54

:49

73.47.80

5 N

017.48

.791

 W28

9.4

9.16

276

Station 25

DA17

‐NG‐ST2

5‐27

6uCT

DuC

TD 

Success

2017

‐09‐25

T12:58

:58

73.47.49

3 N

017.46

.812

 W29

3.5

2017

‐09‐25

T13:06

:22

73.46.93

5 N

017.43

.213

 W28

6.8

7.86

277

Station 25

DA17

‐NG‐ST2

5‐27

7uCT

DuC

TD 

Success

2017

‐09‐25

T13:10

:35

73.46.60

0 N

017.41

.087

 W28

4.4

2017

‐09‐25

T13:17

:35

73.46.05

6 N

017.37

.661

 W94

2.2

7.43

278

Station 25

DA17

‐NG‐ST2

5‐27

8uCT

DuC

TD 

Success

2017

‐09‐25

T13:22

:35

73.45.67

4 N

017.35

.199

 W27

7.2

2017

‐09‐25

T13:28

:54

73.45.21

2 N

017.32

.189

 W28

1.9

7.8

279

Station 26

DA17

‐NG‐ST2

6‐27

9‐CT

DSEA (CTD

)Su

ccess

2017

‐09‐25

T13:45

:41

73.44.04

9 N

017.27

.222

 W28

3.7

2017

‐09‐25

T14:22

:05

73.43.85

5 N

017.29

.219

 W27

0.4

0.61

280

Station 26

DA17

‐NG‐ST2

6‐28

0uCT

DuC

TD 

Success

2017

‐09‐25

T14:41

:21

73.42.48

7 N

017.23

.770

 W26

6.7

2017

‐09‐25

T14:47

:15

73.41.98

3 N

017.21

.414

 W26

8.9

4.11

281

Station 26

DA17

‐NG‐ST2

6‐28

1uCT

DuC

TD 

Success

2017

‐09‐25

T14:51

:13

73.41.66

9 N

017.19

.729

 W26

8.4

2017

‐09‐25

T14:57

:21

73.41.18

4 N

017.17

.040

 W27

5.6

4.82

282

Station 26

DA17

‐NG‐ST2

6‐28

2uCT

DuC

TD 

Success

2017

‐09‐25

T15:01

:51

73.40.82

1 N

017.15

.007

 W20

53.2

2017

‐09‐25

T15:08

:20

73.40.30

7 N

017.12

.110

 W24

14.8

4.63

283

Station 26

DA17

‐NG‐ST2

6‐28

3uCT

DuC

TD 

Success

2017

‐09‐25

T15:14

:12

73.39.85

6 N

017.09

.489

 W20

43.9

2017

‐09‐25

T15:20

:05

73.39.41

4 N

017.06

.862

 W20

79.5

4.51

284

Station 26

DA17

‐NG‐ST2

6‐28

4uCT

DuC

TD 

Success

2017

‐09‐25

T15:24

:19

73.39.10

4 N

017.04

.961

 W27

320

17‐09‐25

T15:30

:05

73.38.66

9 N

017.02

.326

 W21

44.5

4.94

285

Station 26

DA17

‐NG‐ST2

6‐28

5uCT

DuC

TD 

Success

2017

‐09‐25

T15:34

:14

73.38.34

4 N

017.00

.332

 W26

6.4

2017

‐09‐25

T15:40

:58

73.37.79

9 N

016.57

.081

 W23

21.4

5.03

286

Station 26

DA17

‐NG‐ST2

6‐28

6uCT

DuC

TD 

Success

2017

‐09‐25

T15:45

:21

73.37.44

1 N

016.54

.901

 W24

71.8

2017

‐09‐25

T15:51

:37

73.36.91

7 N

016.51

.950

 W24

54.9

4.92

287

Station 26

DA17

‐NG‐ST2

6‐28

7uCT

DuC

TD 

Success

2017

‐09‐25

T15:56

:08

73.36.53

8 N

016.50

.001

 W21

56.1

2017

‐09‐25

T16:02

:04

73.35.92

4 N

016.47

.950

 W23

32.2

4.02

288

Station 27

DA17

‐NG‐ST2

7‐28

8CTD

SEA (CTD

)Su

ccess

2017

‐09‐25

T16:08

:14

73.35.83

0 N

016.47

.979

 W27

1.6

2017

‐09‐25

T16:42

:42

73.36.13

4 N

016.47

.181

 W27

1.5

5.61

289

Station 27

DA17

‐NG‐ST2

7‐28

9uCT

DuC

TD 

Success

2017

‐09‐25

T17:11

:11

73.34.32

0 N

016.38

.298

 W24

40.6

2017

‐09‐25

T17:17

:32

73.33.72

5 N

016.35

.740

 W20

89.2

10.66

290

Station 27

DA17

‐NG‐ST2

7‐29

0uCT

DuC

TD 

Success

2017

‐09‐25

T17:21

:27

73.33.36

1 N

016.34

.136

 W21

07.2

2017

‐09‐25

T17:29

:16

73.32.62

0 N

016.30

.969

 W19

46.7

10.93

291

Station 27

DA17

‐NG‐ST2

7‐29

1uCT

DuC

TD 

Success

2017

‐09‐25

T17:33

:23

73.32.24

0 N

016.29

.340

 W20

89.5

2017

‐09‐25

T17:40

:12

73.31.60

0 N

016.26

.601

 W21

8714

.71

292

Station 27

DA17

‐NG‐ST2

7‐29

2uCT

DuC

TD 

Success

2017

‐09‐25

T17:44

:52

73.31.17

1 N

016.24

.770

 W19

97.3

2017

‐09‐25

T17:51

:02

73.30.61

5 N

016.22

.405

 W23

62.3

13.04

293

Station 27

DA17

‐NG‐ST2

7‐29

3uCT

DuC

TD 

Success

2017

‐09‐25

T17:55

:42

73.30.17

8 N

016.20

.568

 W22

51.9

2017

‐09‐25

T18:01

:48

73.29.60

1 N

016.18

.166

 W26

214

.06

294

Station 28

DA17

‐NG‐ST2

8‐29

4CTD

SEA (CTD

)Su

ccess

2017

‐09‐25

T18:43

:55

73.27.63

1 N

016.10

.445

 W60

7.1

2017

‐09‐25

T19:42

:27

73.27.64

4 N

016.10

.740

 W23

27.2

8.99

295

Station 28

DA17

‐NG‐ST2

8‐29

5uCT

DuC

TD 

Success

2017

‐09‐25

T20:00

:07

73.26.38

2 N

016.06

.219

 W23

25.4

2017

‐09‐25

T20:11

:21

73.25.19

3 N

016.01

.342

 W20

41.6

11.73

296

Station 28

DA17

‐NG‐ST2

8‐29

6uCT

DuC

TD 

Success

2017

‐09‐25

T20:16

:51

73.24.60

7 N

015.58

.972

 W24

4920

17‐09‐25

T20:29

:57

73.23.23

5 N

015.53

.317

 W19

00.1

13.93

297

Station 28

DA17

‐NG‐ST2

8‐29

7uCT

DuC

TD 

Success

2017

‐09‐25

T20:34

:51

73.22.72

1 N

015.51

.220

 W24

01.9

2017

‐09‐25

T20:46

:26

73.21.64

4 N

015.45

.937

 W18

41.1

13.59

298

Station 29

DA17

‐NG‐ST2

9‐29

8CTD

SEA (CTD

)Fail

2017

‐09‐25

T21:19

:51

73.19.11

3 N

015.34

.288

 W18

01.6

2017

‐09‐25

T21:39

:26

73.19.10

0 N

015.34

.869

 W17

96.3

8.2

299

Station 29

DA17

‐NG‐ST2

9‐29

9WP3

WP3

 Net  

Success

2017

‐09‐25

T21:47

:45

73.19.10

9 N

015.35

.093

 W21

12.3

2017

‐09‐25

T22:31

:34

73.19.01

1 N

015.36

.397

 W17

92.7

7.02

300

Station 29

DA17

‐NG‐ST2

9‐30

0CTD

SEA (CTD

)Su

ccess

2017

‐09‐25

T23:19

:06

73.18.45

0 N

015.33

.789

 W18

36.4

2017

‐09‐25

T23:43

:27

73.18.52

9 N

015.34

.630

 W19

07.2

7.77

53

Dep

loym

ent 

no.

Statiopn

 no.

Nam

eInstrumen

tStatus

Time Start d

eploym

ent 

(UTC

)Latitud

e Start

Long

itude

 Start

Water dep

th 

Start

timeS

top (UTC

)Latitud

e Stop

Long

itude

 Stop

Water dep

th 

Stop

Wind Sp

eed